Physician well-being is vital to delivering high-quality emergency care.A supported and healthy emergency medicine workforce leads to better patient outcomes,fewer medical errors,and greater job satisfaction and staff...Physician well-being is vital to delivering high-quality emergency care.A supported and healthy emergency medicine workforce leads to better patient outcomes,fewer medical errors,and greater job satisfaction and staff retention.[1,2]Emergency physicians(EPs)face unique pressures,including shift work,high patient volumes and acuities,overcrowding,and systemic inefficiencies that escalate their risk of burnout.As a result,EPs have reported the highest rates of burnout among physician specialties.展开更多
BACKGROUND:Acute pain is a sudden experience secondary to injuries and varies in perception among individuals.In trauma patients,it can negatively aff ect respiratory function,immune response,and wound healing,making ...BACKGROUND:Acute pain is a sudden experience secondary to injuries and varies in perception among individuals.In trauma patients,it can negatively aff ect respiratory function,immune response,and wound healing,making it a signifi cant public health concern.This study is to determine the prevalence and factors associated with acute pain among emergency trauma patients.METHODS:A multicenter cross-sectional study was conducted.Data were collected via interviewer-administered questionnaires and patient chart review.The data were analyzed via the statistical package for social science version 25.Bivariable and multivariable logistic regression analyses were used.Variables with a P-value<0.05 were considered statistically signifi cant.RESULTS:A total of 397 patients were included in the study,for a response rate of 96.8%.The prevalence of pain during admission was 91.9%(95%confi dence intervals[95%CIs]:88.8%-94.4%).Blunt trauma(adjusted odds ratio[aOR]=2.82;95%CI:1.23-6.45),analgesia before admission to the emergency department(aOR=2.71;95%CI:1.16-6.36),documentation of pain severity in the chart(aOR=2.71;95%CI:1.16-6.36),analgesia provided within two hours after admission(aOR=7.60;95%CI:2.79-20.68),use of non-pharmacological pain management methods(aOR=3.09;95%CI:1.35-7.08)and availability of analgesia(aOR=3.95;95%CI:1.36-11.43)were associated with acute pain experience.CONCLUSION:The prevalence of acute pain among emergency trauma patients was high in the study area.Analgesia should be administered prior to admission,and non-pharmacological pain management should be implemented.Moreover,training on pain assessment and management should be provided for healthcare providers in the emergency department.展开更多
Objective:To compare the therapeutic efficacy of intravenous pantoprazole and famotidine for the treatment of epigastric pain in patients presenting to the emergency department.Methods:In this triple-blind randomized ...Objective:To compare the therapeutic efficacy of intravenous pantoprazole and famotidine for the treatment of epigastric pain in patients presenting to the emergency department.Methods:In this triple-blind randomized clinical trial,eligible patients presenting with epigastric pain were randomly assigned to receive intravenous pantoprazole or famotidine.Block randomization was used,and patients,treating physicians,and outcome assessors were blinded to treatment allocation.Pain intensity was assessed at baseline and at 30 and 60 minutes after drug administration.Results:Eighty patients were enrolled,with a mean age of 36.6 years(SD,15.0),and 42.5%were male.Mean pain scores decreased significantly over time in both treatment groups.In the pantoprazole group,pain scores declined from 8.02±1.28 at baseline to 4.75±1.31 at 30 minutes and 1.62±1.29 at 60 minutes,whereas in the famotidine group scores decreased from 8.12±1.48 to 5.37±1.23 and 2.35±1.54,respectively.There was no significant difference in baseline pain scores between groups(P=.92).Pantoprazole resulted in greater pain reduction compared with famotidine at both 30 minutes(P=.04)and 60 minutes(P=.05).Conclusions:Both medications were effective in relieving epigastric pain;however,pantoprazole provided greater and more sustained pain reduction,supporting its preferential use in emergency settings.展开更多
Objective:Early sepsis can be treated if recognised early,but progression to severe sepsis and septic shock and multiple organ dysfunction syndrome substantially increases mortality.The objectives of our study were to...Objective:Early sepsis can be treated if recognised early,but progression to severe sepsis and septic shock and multiple organ dysfunction syndrome substantially increases mortality.The objectives of our study were to assess morbidity and mortality of patients with sepsis and to compare the effectiveness of a simple bedside satisfiable Quick Sequential Organ Failure Assessment(qSOFA)score with National Early Warning Score(NEWS)in prognosticating sepsis.Methods:This prospective observational study was conducted among patients>18 years old presenting with sepsis at B.J.Medical College.The SOFA,qSOFA and NEWS scores were calculated.The effectiveness in predicting mortality was evaluated using receiver operating characteristic curve analysis.Results:A total of 200 patients were evaluated(56%male)with a mean age of 51.7 years.The mortality rate was 23%.Patients categorized under high risk according to SOFA score>8,qSOFA score of 2-3 and NEWS>7 had a mortality rate of 33.3%,27.5%and 28.4%,respectively.AUC for mortality prediction was 0.695 using SOFA score,0.665 using qSOFA and 0.725 using NEWS.At a cut off of 7.50,NEWS demonstrated a sensitivity of 97.8%with a specificity of 28.0%and outperformed both SOFA and qSOFA which yielded a sensitivity of 43.5%and 91.3%and a specificity of 77.9%and 27.9%,respectively.Conclusions:The NEWS score outperforms SOFA and qSOFA in predicting mortality among sepsis patients.However,qSOFA is more helpful in identifying high risk patients and performs better in intensive care setting.展开更多
Against the backdrop of continuous social development and growing public health demands,the efficiency and scientific nature of the emergency care system are of paramount importance.This paper focuses on researching t...Against the backdrop of continuous social development and growing public health demands,the efficiency and scientific nature of the emergency care system are of paramount importance.This paper focuses on researching the construction of an emergency care system based on the concept of“linkage”,delving into its theoretical foundations,exploring innovative construction models,and analyzing practical cases.The study indicates that an emergency care system under the“linkage”concept can effectively integrate resources and enhance efficiency,providing new insights for improving the construction of the emergency care system.It aims to promote the development of the emergency care system towards a more scientific,efficient,and collaborative direction.展开更多
Knowledge graphs,which combine structured representation with semantic modeling,have shown great potential in knowledge expression,causal inference,and automated reasoning,and are widely used in fields such as intelli...Knowledge graphs,which combine structured representation with semantic modeling,have shown great potential in knowledge expression,causal inference,and automated reasoning,and are widely used in fields such as intelligent question answering,decision support,and fault diagnosis.As high-speed train systems become increasingly intelligent and interconnected,fault patterns have grown more complex and dynamic.Knowledge graphs offer a promising solution to support the structured management and real-time reasoning of fault knowledge,addressing key requirements such as interpretability,accuracy,and continuous evolution in intelligent diagnostic systems.However,conventional knowledge graph construction relies heavily on domain expertise and specialized tools,resulting in high entry barriers for non-experts and limiting their practical application in frontline maintenance scenarios.To address this limitation,this paper proposes a fault knowledge modeling approach for high-speed trains that integrates structured logic diagrams with knowledge graphs.The method employs a seven-layer logic structure—comprising fault name,applicable vehicles,diagnostic logic,signal parameters,verification conditions,fault causes,and emergency measures—to transform unstructured knowledge into a visual and hierarchical representation.A semantic mapping mechanism is then used to automatically convert logic diagrams into machine-interpretable knowledge graphs,enabling dynamic reasoning and knowledge reuse.Furthermore,the proposed method establishes a three-layer architecture—logic structuring,knowledge graph transformation,and dynamic inference—to bridge human-expert logic with machinebased reasoning.Experimental validation and system implementation demonstrate that this approach not only improves knowledge interpretability and inference precision but also significantly enhances modeling efficiency and system maintainability.It provides a scalable and adaptable solution for intelligent operation and maintenance platforms in the high-speed rail domain.展开更多
BACKGROUND Appropriate care for individuals who attempt suicide and are admitted to the emergency department(ED)can prevent future suicidal behavior.It is vital to understand their sociodemographic characteristics and...BACKGROUND Appropriate care for individuals who attempt suicide and are admitted to the emergency department(ED)can prevent future suicidal behavior.It is vital to understand their sociodemographic characteristics and the effects of targeted psychological care.AIM To analyze sociodemographic characteristics of suicide attempters treated in the ED and evaluate the efficacy of psychological care.METHODS Data from 239 suicide attempters treated in the ED of the Central Hospital of Enshi Tujia and Miao Autonomous Prefecture(Hubei Province,China)between January 2021 and February 2025 were divided into 2:Control(n=108)and psychological care(n=131).The demographic characteristics and effects of the psychological care were analyzed.RESULTS The mean(±SD)age of the 239 patients[114 male(47.7%),125 female(52.3%)]was 26.25±9.3 years,of whom 122(45.2%)were single,117(48.9%)were married,and 106(44.4%)had secondary education.Thirty-eight(15.9%)patients had suicidal intent,with a mean of 1.26±0.59 suicide attempts each.Twenty-two(9.21%)patients had a family history of suicide,while 8(3.34%)had a family history of suicide attempt(s).Before intervention,mean Suicidal Intent Scale scores in the psychological nursing and control groups were 21.57±5.28 and 19.86±5.92,respectively(P>0.05).After 1 month of nursing intervention,the respective scores were 10.09±1.11 and 16.48±0.87(P<0.001);and the re-suicide rates were 11.45%(15/131)and 24.07%(26/108)(P<0.001).CONCLUSION Psychological care significantly reduces suicide risk;EDs should provide comprehensive mental health care.展开更多
BACKGROUND:This study aims to develop and validate a machine learning-based in-hospital mortality predictive model for acute aortic syndrome(AAS)in the emergency department(ED)and to derive a simplifi ed version suita...BACKGROUND:This study aims to develop and validate a machine learning-based in-hospital mortality predictive model for acute aortic syndrome(AAS)in the emergency department(ED)and to derive a simplifi ed version suitable for rapid clinical application.METHODS:In this multi-center retrospective cohort study,AAS patient data from three hospitals were analyzed.The modeling cohort included data from the First Affiliated Hospital of Zhengzhou University and the People’s Hospital of Xinjiang Uygur Autonomous Region,with Peking University Third Hospital data serving as the external test set.Four machine learning algorithms—logistic regression(LR),multilayer perceptron(MLP),Gaussian naive Bayes(GNB),and random forest(RF)—were used to develop predictive models based on 34 early-accessible clinical variables.A simplifi ed model was then derived based on fi ve key variables(Stanford type,pericardial eff usion,asymmetric peripheral arterial pulsation,decreased bowel sounds,and dyspnea)via Least Absolute Shrinkage and Selection Operator(LASSO)regression to improve ED applicability.RESULTS:A total of 929 patients were included in the modeling cohort,and 210 were included in the external test set.Four machine learning models based on 34 clinical variables were developed,achieving internal and external validation AUCs of 0.85-0.90 and 0.73-0.85,respectively.The simplifi ed model incorporating fi ve key variables demonstrated internal and external validation AUCs of 0.71-0.86 and 0.75-0.78,respectively.Both models showed robust calibration and predictive stability across datasets.CONCLUSION:Both kinds of models were built based on machine learning tools,and proved to have certain prediction performance and extrapolation.展开更多
Aortic saddle embolism(ASE)is a rare but catastrophic vascular emergency characterized by acute occlusion of the aortic bifurcation,leading to bilateral lower limb ischemia and multiorgan dysfunction.Despite advances ...Aortic saddle embolism(ASE)is a rare but catastrophic vascular emergency characterized by acute occlusion of the aortic bifurcation,leading to bilateral lower limb ischemia and multiorgan dysfunction.Despite advances in imaging and surgical techniques,ASE has high morbidity and mortality rates,particularly when diagnosis or intervention is delayed.Here,we report two patients admitted to our center to increase awareness among emergency physicians.展开更多
This study investigated the application and the application value of intelligent emergency in emergency management in the big data environment.It addresses the neglect of the application value(performance)measurement ...This study investigated the application and the application value of intelligent emergency in emergency management in the big data environment.It addresses the neglect of the application value(performance)measurement of intelligent emergency,further improving the effectiveness of intelligent emergency management.First,approximately 3,900 documents from the intelligent emergency field are analyzed to determine the future research trend in intelligent emergency management.The socio-technical theory concerning technical and social systems is introduced.The emergency management system concepts of“technology enabling”and“enabling value creation”are defined according to bibliometric analysis and socio-technical theory.Second,a research framework that includes technology enabling and enabling value creation for the decision-making paradigm in emergency management according to the big data environment is constructed.A detailed analysis approach from intelligent emergency technology enabling to enabling value creation in emergency management is proposed.Finally,earthquake disasters are taken as examples,and specific analyses of the intelligent emergency enabling and enabling value creation are explored;enabling value creation is discussed based on measurable indicators.The clear concept of emergency management system technology enabling and enabling value creation,as well as the detailed analysis approach from intelligent emergency technology enabling to enabling value creation,provide a theoretical bases for scholars and practitioners to evaluate the value(performance)of intelligent emergency for the first time.展开更多
BACKGROUND:Tracheal intubation(TI)is a fundamental procedure for securing the airway or assisting ventilation in emergency medicine.Tracheal intubation in the lateral position(TILP)has been utilized in clinical practi...BACKGROUND:Tracheal intubation(TI)is a fundamental procedure for securing the airway or assisting ventilation in emergency medicine.Tracheal intubation in the lateral position(TILP)has been utilized in clinical practice,demonstrating potential advantages in specific scenarios,including emergency settings.However,there is a lack of comprehensive reviews and practical protocols on TILP application.To address this gap,we performed a narrative review,and provided evidence-based recommendations to formulate a practice protocol,to assist clinicians to effectively apply TILP.METHODS:We conducted a narrative review of TILP applications and developed recommendations based on clinical research evidence and clinical experience.Delphi method was used among the TILP consortium to grade the strength of the recommendations and to help reach consensus.The practice protocols were formulated as warranted by advancements in medical knowledge,technology,and practice.RESULTS:This narrative review summarized the current evidence on TILP application,highlighting its safety,efficacy,challenges,and potential complications.In total,24 recommendations and a clinical protocol for TILP application in emergency patients were established.CONCLUSION:TILP is a valuable technique in emergency medicine.We reviewed its application in emergency settings and formulated recommendations along with a clinical practice protocol.Future studies are needed to evaluate the safety and efficacy of TILP,broaden its scope of application,and explore effective training protocols.展开更多
The BOPPPS teaching model is a student-centered teaching model that has been widely applied in various teaching fields.This paper summarizes the overview of the BOPPPS teaching model,its application in emergency teach...The BOPPPS teaching model is a student-centered teaching model that has been widely applied in various teaching fields.This paper summarizes the overview of the BOPPPS teaching model,its application in emergency teaching and training,as well as its advantages and disadvantages,aiming to provide references for the further promotion and application of the BOPPPS teaching model in emergency education.展开更多
BACKGROUND:Large language models(LLMs)are being explored for disease prediction and diagnosis;however,their effi cacy for early sepsis identifi cation in emergency departments(EDs)remains unexplored.This study aims to...BACKGROUND:Large language models(LLMs)are being explored for disease prediction and diagnosis;however,their effi cacy for early sepsis identifi cation in emergency departments(EDs)remains unexplored.This study aims to evaluate MedGo,a novel medical LLM,as a decision-support tool for clinicians managing patients with suspected sepsis.METHODS:This retrospective study included anonymized medical records of 203 patients(mean age 79.9±10.2 years)with confi rmed sepsis from a tertiary hospital ED between January 2023 and January 2024.MedGo performance across nine sepsis-related assessment tasks was compared with that of two junior(<3 years of experience)and two senior(>10 years of experience)ED physicians.Assessments were scored on a 5-point Likert scale for accuracy,comprehensiveness,readability,and case-analysis skills.RESULTS:MedGo demonstrated diagnostic performance comparable to that of senior physicians across most metrics,achieving a median Likert score of 4 in accuracy,comprehensiveness,and readability.MedGo signifi cantly outperformed junior physicians(P<0.001 for accuracy and case-analysis skills).MedGo assistance significantly enhanced both junior(P<0.001)and senior(P<0.05)physicians'diagnostic accuracy.Notably,MedGo-assisted junior physicians achieved accuracy levels comparable to those of unassisted senior physicians.MedGo maintained consistent performance across varying sepsis severities.CONCLUSION:MedGo shows significant diagnostic efficacy for sepsis and effectively supports clinicians in the ED,particularly enhancing junior physicians’performance.Our study highlights the potential of MedGo as a valuable decision-support tool for sepsis management,paving the way for specialized sepsis AI models.展开更多
The rapid evolution of Fifth-Generation(5G)networks and the strategic development of Sixth-Generation(6G)technologies have significantly advanced the implementation of air-ground integrated networks with seamless cove...The rapid evolution of Fifth-Generation(5G)networks and the strategic development of Sixth-Generation(6G)technologies have significantly advanced the implementation of air-ground integrated networks with seamless coverage.Unmanned Aerial Vehicles(UAVs),serving as high-mobility aerial platforms,are extensively utilized to enhance coverage in long-distance emergency communication scenarios.The resource-constrained communication environments in emergencies by classifying UAVs into swarm UAVs and relay UAVs as aerial communication nodes is inversitgated.A horizontal deployment strategy for swarm UAVs is formulated through K-means clustering algorithm optimization,while a vertical deployment scheme is established using convex optimization methods.The minimum-path trajectory planning for relay UAVs is optimized via the Particle Swarm Optimization(PSO)algorithm,enhancing communication reliability between UAV swarms and terrestrial base stations.A three-dimensional heterogeneous network architecture is realized by modeling spatial multi-hop relay links.Experimental results demonstrate that the proposed joint UAV relay optimization framework outperforms conventional algorithms in both coverage performance and relay capability during video stream transmission,achieving significant improvements in coverage enhancement and relay efficiency.This work provides technical foundations for constructing high-reliability air-ground cooperative systems in emergency communications.展开更多
Shotcrete is one of the common solutions for shallow sliding.It works by forming a protective layer with high strength and cementing the loose soil particles on the slope surface to prevent shallow sliding.However,the...Shotcrete is one of the common solutions for shallow sliding.It works by forming a protective layer with high strength and cementing the loose soil particles on the slope surface to prevent shallow sliding.However,the solidification time of conventional cement paste is long when shotcrete is used to treat cohesionless soil landslide.The idea of reinforcing slope with polyurethane solidified soil(i.e.,mixture of polyurethane and sand)was proposed.Model tests and finite element analysis were carried out to study the effectiveness of the proposed new method on the emergency treatment of cohesionless soil landslide.Surcharge loading on the crest of the slope was applied step by step until landslide was triggered so as to test and compare the stability and bearing capacity of slope models with different conditions.The simulated slope displacements were relatively close to the measured results,and the simulated slope deformation characteristics were in good agreement with the observed phenomena,which verifies the accuracy of the numerical method.Under the condition of surcharge loading on the crest of the slope,the unreinforced slope slid when the surcharge loading exceeded 30 k Pa,which presented a failure mode of local instability and collapse at the shallow layer of slope top.The reinforced slope remained stable even when the surcharge loading reached 48 k Pa.The displacement of the reinforced slope was reduced by more than 95%.Overall,this study verifies the effectiveness of polyurethane in the emergency treatment of cohesionless soil landslide and should have broad application prospects in the field of geological disasters concerning the safety of people's live.展开更多
Typhoons can cause large-area blackouts or partial outages of distribution networks.We define a partial outage state in the distribution network as a gray state and propose a gray-start strategy and two-stage distribu...Typhoons can cause large-area blackouts or partial outages of distribution networks.We define a partial outage state in the distribution network as a gray state and propose a gray-start strategy and two-stage distribution network emergency recovery framework.A phase-space reconstruction and stacked integrated model for predicting wind and photovoltaic generation during typhoon disasters is proposed in the first stage.This provides guidance for second-stage post-disaster emergency recovery scheduling.The emergency recovery scheduling model is established in the second stage,and this model is supported by a thermal power-generating unit,mobile emergency generators,and distributed generators.Distributed generation includes wind power generation,photovoltaics,fuel cells,etc.Simultaneously,we con-sider the gray-start based on the pumped storage unit to be an important first step in the emergency recovery strategy.This model is val-idated on the improved IEEE 33 node system,which utilizes data from the 2022 super typhoon“Muifa”in Zhoushan,Zhejiang,China.Simulations indicate the superiority of a gray start with a pumped storage unit and the proposed emergency recovery strategy.展开更多
Emergency department nurses face severe occupational stress leading to anxiety,depression,and burnout,which significantly impair their well-being and patientcare quality.This narrative review examined the role of mind...Emergency department nurses face severe occupational stress leading to anxiety,depression,and burnout,which significantly impair their well-being and patientcare quality.This narrative review examined the role of mindfulness-based stress reduction(MBSR)in addressing these challenges.Rooted in nonjudgmental present-moment awareness,MBSR enhances emotional regulation and reduces psychological distress by fostering adaptive coping strategies.Studies have demonstrated its efficacy in lowering anxiety,depressive symptoms,and emotional exhaustion,while improving workplace well-being,empathy,and job satisfaction.Mechanistically,MBSR improves interoceptive awareness and autonomic balance,as evidenced by physiological markers such as heart rate variability.However,gaps remain in long-term efficacy assessments,personalized interventions,and integration with multidisciplinary approaches.Future research should prioritize tailored biomarker-driven programs,longitudinal studies,and scalable implementation strategies in high-stress clinical settings.This review underscores MBSR’s potential as a sustainable,evidence-based tool to enhance emergency department nurses’mental health and professional performance,advocating for broader adoption and further refinement of its practical applications.展开更多
Introduction: Head injuries constitute a public health problem in Cameroon and everywhere else in the world. They represent 23% of admissions to the Yaounde emergency center (CURY), which is a center exclusively dedic...Introduction: Head injuries constitute a public health problem in Cameroon and everywhere else in the world. They represent 23% of admissions to the Yaounde emergency center (CURY), which is a center exclusively dedicated, since 2014, to emergency care in Yaounde. In the management of trauma brain injuries at CURY, several are operated on. However, to date, no evaluation of these operated patients has yet been made. Goals: The objective of this study was to highlight the prognostic factors in patients operated for TBI at CURY. Methodology: We conducted a descriptive study whose data collection was done retrospectively over 2 years (01 January 2021 to 31 December 2022) at CURY. Data was collected from the registers of operative reports. Results: We enrolled 105 medical reports of patients who were victims of TBI operated on. The male gender predominated with a sex ratio of 3/1. The average age of the patients was 37.5 ± 18.83 years. Public road accidents were the leading cause of TBI in 75.2% of cases. The means of transport of the victims were mostly non-medical 97.1%. 45.7% of patients were admitted in less than 6 hours following injury. The initial clinical evaluation found 45.8% of patients with a Glasgow Coma Score (GCS) between [14, 15], and 13.2% of patients had a GCS 8. The indications for surgery were extradural hematoma (30%), followed by acute subdural hematoma (24%). The major complication was postoperative infection (25%). The mortality rate of the series was 7.9%. Poor prognostic factors were the depth of the coma on admission, advanced age and postoperative complications. Conclusion: The results of this study suggest that most patients operated on for TBI at CURY had a favorable outcome. The poor prognostic factors were the depth of the coma on admission, advanced age, postoperative complications and comorbidities.展开更多
Introduction and Problem Statement: Many medication errors occur during the community and hospital transition. Indeed, the World Health Organization launched the international “High 5S” project to implement medicati...Introduction and Problem Statement: Many medication errors occur during the community and hospital transition. Indeed, the World Health Organization launched the international “High 5S” project to implement medication reconciliation in healthcare facilities to reduce them and ensure patients a safe, high-quality healthcare pathway. Objective: This study aimed to detect medication errors by reconciling drug treatments and assess the relevance and feasibility of this standardized practice within the Medical Emergency Unit of the Teaching Pediatric Hospital of Ouagadougou (Burkina Faso). Methods: Patients whose parents gave their consent at their entrance were enrolled. For each patient, the pharmacy team completed a reconciliation form that included the patient’s usual treatment, which was taken and in progress and received upon admission to the medical emergency unit. Patients’ treatments were reviewed to detect and characterize discrepancies. The data of each form were reported and analyzed using KoboCollect, an Android application. Results: 135 records and 412 medication lines were captured over six weeks. The average time of treatment reconciliation per patient was 57 minutes. One thousand one hundred ninety-eight (1198) intentional discrepancies were detected, of which 6.09% were documented. Seventy-one (71) unintentional discrepancies were collected, including 39 omissions, 24 regimen dosing errors, and 8 pharmaceutical form dosage errors. Forty-nine (49) unintentional discrepancies, or 69.01%, were corrected by formulated pharmaceutical interventions toward physicians. Conclusion: Medical treatment reconciliation during hospital admission is critical because discrepancies can compromise the efficacy and/or safety of the patient’s hospital medication.展开更多
There is increasing research into the potential benefits of incorporating artificial intelligence(AI)and machine learning algorithms into emergency medical services.AI is finding new applications across a wide range o...There is increasing research into the potential benefits of incorporating artificial intelligence(AI)and machine learning algorithms into emergency medical services.AI is finding new applications across a wide range of sectors,one of which is healthcare,where it is being used to enhance clinical diagnostics.AI solutions have enormous untapped potential to improve healthcare efficiency and quality,thus researchers have focused heavily on emergency medicine(EM).Many individuals without prior experience with any physician often receive their initial medical care in the emergency room.Two areas that could benefit from the implementation of AI are reducing waiting times and enhancing diagnostic capabilities.This study provides further explanation of how AI is used in emergency rooms.Several machine learning‐based algorithms are also addressed.In this research,we summarise recent developments in the use of AI in EM.This research tries to summarise the usefulness of AI in EM by looking at recent developments in emergency department operations and clinical patient management.展开更多
文摘Physician well-being is vital to delivering high-quality emergency care.A supported and healthy emergency medicine workforce leads to better patient outcomes,fewer medical errors,and greater job satisfaction and staff retention.[1,2]Emergency physicians(EPs)face unique pressures,including shift work,high patient volumes and acuities,overcrowding,and systemic inefficiencies that escalate their risk of burnout.As a result,EPs have reported the highest rates of burnout among physician specialties.
文摘BACKGROUND:Acute pain is a sudden experience secondary to injuries and varies in perception among individuals.In trauma patients,it can negatively aff ect respiratory function,immune response,and wound healing,making it a signifi cant public health concern.This study is to determine the prevalence and factors associated with acute pain among emergency trauma patients.METHODS:A multicenter cross-sectional study was conducted.Data were collected via interviewer-administered questionnaires and patient chart review.The data were analyzed via the statistical package for social science version 25.Bivariable and multivariable logistic regression analyses were used.Variables with a P-value<0.05 were considered statistically signifi cant.RESULTS:A total of 397 patients were included in the study,for a response rate of 96.8%.The prevalence of pain during admission was 91.9%(95%confi dence intervals[95%CIs]:88.8%-94.4%).Blunt trauma(adjusted odds ratio[aOR]=2.82;95%CI:1.23-6.45),analgesia before admission to the emergency department(aOR=2.71;95%CI:1.16-6.36),documentation of pain severity in the chart(aOR=2.71;95%CI:1.16-6.36),analgesia provided within two hours after admission(aOR=7.60;95%CI:2.79-20.68),use of non-pharmacological pain management methods(aOR=3.09;95%CI:1.35-7.08)and availability of analgesia(aOR=3.95;95%CI:1.36-11.43)were associated with acute pain experience.CONCLUSION:The prevalence of acute pain among emergency trauma patients was high in the study area.Analgesia should be administered prior to admission,and non-pharmacological pain management should be implemented.Moreover,training on pain assessment and management should be provided for healthcare providers in the emergency department.
文摘Objective:To compare the therapeutic efficacy of intravenous pantoprazole and famotidine for the treatment of epigastric pain in patients presenting to the emergency department.Methods:In this triple-blind randomized clinical trial,eligible patients presenting with epigastric pain were randomly assigned to receive intravenous pantoprazole or famotidine.Block randomization was used,and patients,treating physicians,and outcome assessors were blinded to treatment allocation.Pain intensity was assessed at baseline and at 30 and 60 minutes after drug administration.Results:Eighty patients were enrolled,with a mean age of 36.6 years(SD,15.0),and 42.5%were male.Mean pain scores decreased significantly over time in both treatment groups.In the pantoprazole group,pain scores declined from 8.02±1.28 at baseline to 4.75±1.31 at 30 minutes and 1.62±1.29 at 60 minutes,whereas in the famotidine group scores decreased from 8.12±1.48 to 5.37±1.23 and 2.35±1.54,respectively.There was no significant difference in baseline pain scores between groups(P=.92).Pantoprazole resulted in greater pain reduction compared with famotidine at both 30 minutes(P=.04)and 60 minutes(P=.05).Conclusions:Both medications were effective in relieving epigastric pain;however,pantoprazole provided greater and more sustained pain reduction,supporting its preferential use in emergency settings.
文摘Objective:Early sepsis can be treated if recognised early,but progression to severe sepsis and septic shock and multiple organ dysfunction syndrome substantially increases mortality.The objectives of our study were to assess morbidity and mortality of patients with sepsis and to compare the effectiveness of a simple bedside satisfiable Quick Sequential Organ Failure Assessment(qSOFA)score with National Early Warning Score(NEWS)in prognosticating sepsis.Methods:This prospective observational study was conducted among patients>18 years old presenting with sepsis at B.J.Medical College.The SOFA,qSOFA and NEWS scores were calculated.The effectiveness in predicting mortality was evaluated using receiver operating characteristic curve analysis.Results:A total of 200 patients were evaluated(56%male)with a mean age of 51.7 years.The mortality rate was 23%.Patients categorized under high risk according to SOFA score>8,qSOFA score of 2-3 and NEWS>7 had a mortality rate of 33.3%,27.5%and 28.4%,respectively.AUC for mortality prediction was 0.695 using SOFA score,0.665 using qSOFA and 0.725 using NEWS.At a cut off of 7.50,NEWS demonstrated a sensitivity of 97.8%with a specificity of 28.0%and outperformed both SOFA and qSOFA which yielded a sensitivity of 43.5%and 91.3%and a specificity of 77.9%and 27.9%,respectively.Conclusions:The NEWS score outperforms SOFA and qSOFA in predicting mortality among sepsis patients.However,qSOFA is more helpful in identifying high risk patients and performs better in intensive care setting.
文摘Against the backdrop of continuous social development and growing public health demands,the efficiency and scientific nature of the emergency care system are of paramount importance.This paper focuses on researching the construction of an emergency care system based on the concept of“linkage”,delving into its theoretical foundations,exploring innovative construction models,and analyzing practical cases.The study indicates that an emergency care system under the“linkage”concept can effectively integrate resources and enhance efficiency,providing new insights for improving the construction of the emergency care system.It aims to promote the development of the emergency care system towards a more scientific,efficient,and collaborative direction.
基金support from the Scientific Funding for the Center of National Railway Intelligent Transportation System Engineering and Technology,China Academy of Railway Sciences Corporation Limited(Grant No.2023YJ354)。
文摘Knowledge graphs,which combine structured representation with semantic modeling,have shown great potential in knowledge expression,causal inference,and automated reasoning,and are widely used in fields such as intelligent question answering,decision support,and fault diagnosis.As high-speed train systems become increasingly intelligent and interconnected,fault patterns have grown more complex and dynamic.Knowledge graphs offer a promising solution to support the structured management and real-time reasoning of fault knowledge,addressing key requirements such as interpretability,accuracy,and continuous evolution in intelligent diagnostic systems.However,conventional knowledge graph construction relies heavily on domain expertise and specialized tools,resulting in high entry barriers for non-experts and limiting their practical application in frontline maintenance scenarios.To address this limitation,this paper proposes a fault knowledge modeling approach for high-speed trains that integrates structured logic diagrams with knowledge graphs.The method employs a seven-layer logic structure—comprising fault name,applicable vehicles,diagnostic logic,signal parameters,verification conditions,fault causes,and emergency measures—to transform unstructured knowledge into a visual and hierarchical representation.A semantic mapping mechanism is then used to automatically convert logic diagrams into machine-interpretable knowledge graphs,enabling dynamic reasoning and knowledge reuse.Furthermore,the proposed method establishes a three-layer architecture—logic structuring,knowledge graph transformation,and dynamic inference—to bridge human-expert logic with machinebased reasoning.Experimental validation and system implementation demonstrate that this approach not only improves knowledge interpretability and inference precision but also significantly enhances modeling efficiency and system maintainability.It provides a scalable and adaptable solution for intelligent operation and maintenance platforms in the high-speed rail domain.
文摘BACKGROUND Appropriate care for individuals who attempt suicide and are admitted to the emergency department(ED)can prevent future suicidal behavior.It is vital to understand their sociodemographic characteristics and the effects of targeted psychological care.AIM To analyze sociodemographic characteristics of suicide attempters treated in the ED and evaluate the efficacy of psychological care.METHODS Data from 239 suicide attempters treated in the ED of the Central Hospital of Enshi Tujia and Miao Autonomous Prefecture(Hubei Province,China)between January 2021 and February 2025 were divided into 2:Control(n=108)and psychological care(n=131).The demographic characteristics and effects of the psychological care were analyzed.RESULTS The mean(±SD)age of the 239 patients[114 male(47.7%),125 female(52.3%)]was 26.25±9.3 years,of whom 122(45.2%)were single,117(48.9%)were married,and 106(44.4%)had secondary education.Thirty-eight(15.9%)patients had suicidal intent,with a mean of 1.26±0.59 suicide attempts each.Twenty-two(9.21%)patients had a family history of suicide,while 8(3.34%)had a family history of suicide attempt(s).Before intervention,mean Suicidal Intent Scale scores in the psychological nursing and control groups were 21.57±5.28 and 19.86±5.92,respectively(P>0.05).After 1 month of nursing intervention,the respective scores were 10.09±1.11 and 16.48±0.87(P<0.001);and the re-suicide rates were 11.45%(15/131)and 24.07%(26/108)(P<0.001).CONCLUSION Psychological care significantly reduces suicide risk;EDs should provide comprehensive mental health care.
基金supported by the special fund of the National Clinical Key Specialty Construction Program[(2022)301-2305].
文摘BACKGROUND:This study aims to develop and validate a machine learning-based in-hospital mortality predictive model for acute aortic syndrome(AAS)in the emergency department(ED)and to derive a simplifi ed version suitable for rapid clinical application.METHODS:In this multi-center retrospective cohort study,AAS patient data from three hospitals were analyzed.The modeling cohort included data from the First Affiliated Hospital of Zhengzhou University and the People’s Hospital of Xinjiang Uygur Autonomous Region,with Peking University Third Hospital data serving as the external test set.Four machine learning algorithms—logistic regression(LR),multilayer perceptron(MLP),Gaussian naive Bayes(GNB),and random forest(RF)—were used to develop predictive models based on 34 early-accessible clinical variables.A simplifi ed model was then derived based on fi ve key variables(Stanford type,pericardial eff usion,asymmetric peripheral arterial pulsation,decreased bowel sounds,and dyspnea)via Least Absolute Shrinkage and Selection Operator(LASSO)regression to improve ED applicability.RESULTS:A total of 929 patients were included in the modeling cohort,and 210 were included in the external test set.Four machine learning models based on 34 clinical variables were developed,achieving internal and external validation AUCs of 0.85-0.90 and 0.73-0.85,respectively.The simplifi ed model incorporating fi ve key variables demonstrated internal and external validation AUCs of 0.71-0.86 and 0.75-0.78,respectively.Both models showed robust calibration and predictive stability across datasets.CONCLUSION:Both kinds of models were built based on machine learning tools,and proved to have certain prediction performance and extrapolation.
文摘Aortic saddle embolism(ASE)is a rare but catastrophic vascular emergency characterized by acute occlusion of the aortic bifurcation,leading to bilateral lower limb ischemia and multiorgan dysfunction.Despite advances in imaging and surgical techniques,ASE has high morbidity and mortality rates,particularly when diagnosis or intervention is delayed.Here,we report two patients admitted to our center to increase awareness among emergency physicians.
基金the National Natural Science Foundation of China(Grant No.:71771061).
文摘This study investigated the application and the application value of intelligent emergency in emergency management in the big data environment.It addresses the neglect of the application value(performance)measurement of intelligent emergency,further improving the effectiveness of intelligent emergency management.First,approximately 3,900 documents from the intelligent emergency field are analyzed to determine the future research trend in intelligent emergency management.The socio-technical theory concerning technical and social systems is introduced.The emergency management system concepts of“technology enabling”and“enabling value creation”are defined according to bibliometric analysis and socio-technical theory.Second,a research framework that includes technology enabling and enabling value creation for the decision-making paradigm in emergency management according to the big data environment is constructed.A detailed analysis approach from intelligent emergency technology enabling to enabling value creation in emergency management is proposed.Finally,earthquake disasters are taken as examples,and specific analyses of the intelligent emergency enabling and enabling value creation are explored;enabling value creation is discussed based on measurable indicators.The clear concept of emergency management system technology enabling and enabling value creation,as well as the detailed analysis approach from intelligent emergency technology enabling to enabling value creation,provide a theoretical bases for scholars and practitioners to evaluate the value(performance)of intelligent emergency for the first time.
基金National Natural Science Foundation of China(U24A20714 to XMF and 82102238 to PC)。
文摘BACKGROUND:Tracheal intubation(TI)is a fundamental procedure for securing the airway or assisting ventilation in emergency medicine.Tracheal intubation in the lateral position(TILP)has been utilized in clinical practice,demonstrating potential advantages in specific scenarios,including emergency settings.However,there is a lack of comprehensive reviews and practical protocols on TILP application.To address this gap,we performed a narrative review,and provided evidence-based recommendations to formulate a practice protocol,to assist clinicians to effectively apply TILP.METHODS:We conducted a narrative review of TILP applications and developed recommendations based on clinical research evidence and clinical experience.Delphi method was used among the TILP consortium to grade the strength of the recommendations and to help reach consensus.The practice protocols were formulated as warranted by advancements in medical knowledge,technology,and practice.RESULTS:This narrative review summarized the current evidence on TILP application,highlighting its safety,efficacy,challenges,and potential complications.In total,24 recommendations and a clinical protocol for TILP application in emergency patients were established.CONCLUSION:TILP is a valuable technique in emergency medicine.We reviewed its application in emergency settings and formulated recommendations along with a clinical practice protocol.Future studies are needed to evaluate the safety and efficacy of TILP,broaden its scope of application,and explore effective training protocols.
基金Scientific Research Program of Tianjin Municipal Education Commission(2023SK011)。
文摘The BOPPPS teaching model is a student-centered teaching model that has been widely applied in various teaching fields.This paper summarizes the overview of the BOPPPS teaching model,its application in emergency teaching and training,as well as its advantages and disadvantages,aiming to provide references for the further promotion and application of the BOPPPS teaching model in emergency education.
基金supported by grants from the National Natural Science Foundation of China(82470074 to LT)the municipal Natural Science Foundation of Shanghai Scientific Committee of China(22ZR1451000 to LT)+6 种基金the Peak Supporting Clinical Discipline of Shanghai Health Bureau(2023ZDFC0104 to LT)the Medical Discipline Construction Program of Shanghai Pudong New Area Health Commission(the Key Disciplines Program,PWZxk2022-17 to LT)the Scientifi c Research Program of Shanghai Pudong New Area Health Commission(the Joint Research and Development Program,PW2023D-07 to LT)the Healthcare Talents Elite Program of Shanghai Pudong New Area(2025PDWSYCBJ-03 to LT)the Youth Science and Technology Program of Shanghai Pudong New Area(PW2024B-11 to CX)the People’s Livelihood Research Project of Shanghai Pudong Science and Economy Commission(PKJ2023-Y39 to DZ)the Scientifi c Research Program of Shanghai Pudong New Area Health Commission(the Science Popularization Program,PWKP2024B-19 to XL).
文摘BACKGROUND:Large language models(LLMs)are being explored for disease prediction and diagnosis;however,their effi cacy for early sepsis identifi cation in emergency departments(EDs)remains unexplored.This study aims to evaluate MedGo,a novel medical LLM,as a decision-support tool for clinicians managing patients with suspected sepsis.METHODS:This retrospective study included anonymized medical records of 203 patients(mean age 79.9±10.2 years)with confi rmed sepsis from a tertiary hospital ED between January 2023 and January 2024.MedGo performance across nine sepsis-related assessment tasks was compared with that of two junior(<3 years of experience)and two senior(>10 years of experience)ED physicians.Assessments were scored on a 5-point Likert scale for accuracy,comprehensiveness,readability,and case-analysis skills.RESULTS:MedGo demonstrated diagnostic performance comparable to that of senior physicians across most metrics,achieving a median Likert score of 4 in accuracy,comprehensiveness,and readability.MedGo signifi cantly outperformed junior physicians(P<0.001 for accuracy and case-analysis skills).MedGo assistance significantly enhanced both junior(P<0.001)and senior(P<0.05)physicians'diagnostic accuracy.Notably,MedGo-assisted junior physicians achieved accuracy levels comparable to those of unassisted senior physicians.MedGo maintained consistent performance across varying sepsis severities.CONCLUSION:MedGo shows significant diagnostic efficacy for sepsis and effectively supports clinicians in the ED,particularly enhancing junior physicians’performance.Our study highlights the potential of MedGo as a valuable decision-support tool for sepsis management,paving the way for specialized sepsis AI models.
文摘The rapid evolution of Fifth-Generation(5G)networks and the strategic development of Sixth-Generation(6G)technologies have significantly advanced the implementation of air-ground integrated networks with seamless coverage.Unmanned Aerial Vehicles(UAVs),serving as high-mobility aerial platforms,are extensively utilized to enhance coverage in long-distance emergency communication scenarios.The resource-constrained communication environments in emergencies by classifying UAVs into swarm UAVs and relay UAVs as aerial communication nodes is inversitgated.A horizontal deployment strategy for swarm UAVs is formulated through K-means clustering algorithm optimization,while a vertical deployment scheme is established using convex optimization methods.The minimum-path trajectory planning for relay UAVs is optimized via the Particle Swarm Optimization(PSO)algorithm,enhancing communication reliability between UAV swarms and terrestrial base stations.A three-dimensional heterogeneous network architecture is realized by modeling spatial multi-hop relay links.Experimental results demonstrate that the proposed joint UAV relay optimization framework outperforms conventional algorithms in both coverage performance and relay capability during video stream transmission,achieving significant improvements in coverage enhancement and relay efficiency.This work provides technical foundations for constructing high-reliability air-ground cooperative systems in emergency communications.
基金the financial support from the Fujian Science Foundation for Outstanding Youth(2023J06039)the National Natural Science Foundation of China(Grant No.41977259,U2005205,41972268)the Independent Research Project of Technology Innovation Center for Monitoring and Restoration Engineering of Ecological Fragile Zone in Southeast China(KY-090000-04-2022-019)。
文摘Shotcrete is one of the common solutions for shallow sliding.It works by forming a protective layer with high strength and cementing the loose soil particles on the slope surface to prevent shallow sliding.However,the solidification time of conventional cement paste is long when shotcrete is used to treat cohesionless soil landslide.The idea of reinforcing slope with polyurethane solidified soil(i.e.,mixture of polyurethane and sand)was proposed.Model tests and finite element analysis were carried out to study the effectiveness of the proposed new method on the emergency treatment of cohesionless soil landslide.Surcharge loading on the crest of the slope was applied step by step until landslide was triggered so as to test and compare the stability and bearing capacity of slope models with different conditions.The simulated slope displacements were relatively close to the measured results,and the simulated slope deformation characteristics were in good agreement with the observed phenomena,which verifies the accuracy of the numerical method.Under the condition of surcharge loading on the crest of the slope,the unreinforced slope slid when the surcharge loading exceeded 30 k Pa,which presented a failure mode of local instability and collapse at the shallow layer of slope top.The reinforced slope remained stable even when the surcharge loading reached 48 k Pa.The displacement of the reinforced slope was reduced by more than 95%.Overall,this study verifies the effectiveness of polyurethane in the emergency treatment of cohesionless soil landslide and should have broad application prospects in the field of geological disasters concerning the safety of people's live.
基金supported in part by the National Nat-ural Science Foundation of China(52177110)Key Pro-gram of the National Natural Science Foundation of China(U22B20106,U2142206)+2 种基金Shenzhen Science and Technology Program(JCYJ20210324131409026)the Science and Technology Project of the State Grid Corpo-ration of China(5200-202319382A-2-3-XG)State Grid Zhejiang Elctric Power Co.,Ltd.Science and Tech-nology Project(B311DS24001A).
文摘Typhoons can cause large-area blackouts or partial outages of distribution networks.We define a partial outage state in the distribution network as a gray state and propose a gray-start strategy and two-stage distribution network emergency recovery framework.A phase-space reconstruction and stacked integrated model for predicting wind and photovoltaic generation during typhoon disasters is proposed in the first stage.This provides guidance for second-stage post-disaster emergency recovery scheduling.The emergency recovery scheduling model is established in the second stage,and this model is supported by a thermal power-generating unit,mobile emergency generators,and distributed generators.Distributed generation includes wind power generation,photovoltaics,fuel cells,etc.Simultaneously,we con-sider the gray-start based on the pumped storage unit to be an important first step in the emergency recovery strategy.This model is val-idated on the improved IEEE 33 node system,which utilizes data from the 2022 super typhoon“Muifa”in Zhoushan,Zhejiang,China.Simulations indicate the superiority of a gray start with a pumped storage unit and the proposed emergency recovery strategy.
文摘Emergency department nurses face severe occupational stress leading to anxiety,depression,and burnout,which significantly impair their well-being and patientcare quality.This narrative review examined the role of mindfulness-based stress reduction(MBSR)in addressing these challenges.Rooted in nonjudgmental present-moment awareness,MBSR enhances emotional regulation and reduces psychological distress by fostering adaptive coping strategies.Studies have demonstrated its efficacy in lowering anxiety,depressive symptoms,and emotional exhaustion,while improving workplace well-being,empathy,and job satisfaction.Mechanistically,MBSR improves interoceptive awareness and autonomic balance,as evidenced by physiological markers such as heart rate variability.However,gaps remain in long-term efficacy assessments,personalized interventions,and integration with multidisciplinary approaches.Future research should prioritize tailored biomarker-driven programs,longitudinal studies,and scalable implementation strategies in high-stress clinical settings.This review underscores MBSR’s potential as a sustainable,evidence-based tool to enhance emergency department nurses’mental health and professional performance,advocating for broader adoption and further refinement of its practical applications.
文摘Introduction: Head injuries constitute a public health problem in Cameroon and everywhere else in the world. They represent 23% of admissions to the Yaounde emergency center (CURY), which is a center exclusively dedicated, since 2014, to emergency care in Yaounde. In the management of trauma brain injuries at CURY, several are operated on. However, to date, no evaluation of these operated patients has yet been made. Goals: The objective of this study was to highlight the prognostic factors in patients operated for TBI at CURY. Methodology: We conducted a descriptive study whose data collection was done retrospectively over 2 years (01 January 2021 to 31 December 2022) at CURY. Data was collected from the registers of operative reports. Results: We enrolled 105 medical reports of patients who were victims of TBI operated on. The male gender predominated with a sex ratio of 3/1. The average age of the patients was 37.5 ± 18.83 years. Public road accidents were the leading cause of TBI in 75.2% of cases. The means of transport of the victims were mostly non-medical 97.1%. 45.7% of patients were admitted in less than 6 hours following injury. The initial clinical evaluation found 45.8% of patients with a Glasgow Coma Score (GCS) between [14, 15], and 13.2% of patients had a GCS 8. The indications for surgery were extradural hematoma (30%), followed by acute subdural hematoma (24%). The major complication was postoperative infection (25%). The mortality rate of the series was 7.9%. Poor prognostic factors were the depth of the coma on admission, advanced age and postoperative complications. Conclusion: The results of this study suggest that most patients operated on for TBI at CURY had a favorable outcome. The poor prognostic factors were the depth of the coma on admission, advanced age, postoperative complications and comorbidities.
文摘Introduction and Problem Statement: Many medication errors occur during the community and hospital transition. Indeed, the World Health Organization launched the international “High 5S” project to implement medication reconciliation in healthcare facilities to reduce them and ensure patients a safe, high-quality healthcare pathway. Objective: This study aimed to detect medication errors by reconciling drug treatments and assess the relevance and feasibility of this standardized practice within the Medical Emergency Unit of the Teaching Pediatric Hospital of Ouagadougou (Burkina Faso). Methods: Patients whose parents gave their consent at their entrance were enrolled. For each patient, the pharmacy team completed a reconciliation form that included the patient’s usual treatment, which was taken and in progress and received upon admission to the medical emergency unit. Patients’ treatments were reviewed to detect and characterize discrepancies. The data of each form were reported and analyzed using KoboCollect, an Android application. Results: 135 records and 412 medication lines were captured over six weeks. The average time of treatment reconciliation per patient was 57 minutes. One thousand one hundred ninety-eight (1198) intentional discrepancies were detected, of which 6.09% were documented. Seventy-one (71) unintentional discrepancies were collected, including 39 omissions, 24 regimen dosing errors, and 8 pharmaceutical form dosage errors. Forty-nine (49) unintentional discrepancies, or 69.01%, were corrected by formulated pharmaceutical interventions toward physicians. Conclusion: Medical treatment reconciliation during hospital admission is critical because discrepancies can compromise the efficacy and/or safety of the patient’s hospital medication.
文摘There is increasing research into the potential benefits of incorporating artificial intelligence(AI)and machine learning algorithms into emergency medical services.AI is finding new applications across a wide range of sectors,one of which is healthcare,where it is being used to enhance clinical diagnostics.AI solutions have enormous untapped potential to improve healthcare efficiency and quality,thus researchers have focused heavily on emergency medicine(EM).Many individuals without prior experience with any physician often receive their initial medical care in the emergency room.Two areas that could benefit from the implementation of AI are reducing waiting times and enhancing diagnostic capabilities.This study provides further explanation of how AI is used in emergency rooms.Several machine learning‐based algorithms are also addressed.In this research,we summarise recent developments in the use of AI in EM.This research tries to summarise the usefulness of AI in EM by looking at recent developments in emergency department operations and clinical patient management.
