This paper explores increased use of the concept of“medical bilingualism”since 2015 as scholars,especially of East Asian medical history and anthropology,have applied it to engagements between two medical systems.It...This paper explores increased use of the concept of“medical bilingualism”since 2015 as scholars,especially of East Asian medical history and anthropology,have applied it to engagements between two medical systems.It reveals an ongoing evolution in the way that scholars understand what a medical system is and how medical systems are differentiated and compared with one another.The image of culturally homogeneous systems of meaning and practice that dominated mid-twentieth-century scholarship on medical systems(especially using the category of ethnomedicines)has been giving way to a more culturally heterogeneous and cosmopolitan picture of how medical practitioners evolve,integrate,and differentiate medical concepts and practices in the context of contemporary societies and the new forms of life they engender.This reformulated concept of medical bilingualism emphasizes the ways in which medical systems overlap yet remain distinct.First,the paper summarizes results of an experiment with AI searches on medical bilingualism,then narrates its historiography both pre-COVID-19 and during COVID-19,and finally concludes with some reflections on language ideology,multilingualism,and medical pluralism.展开更多
China＇s Rural Cooperative Medical System collapsed alongside communal farming at the end of the Maoist period in 1976, leaving most farmers vulnerable[1]. In rural areas, where 80% of people have been without health ...China＇s Rural Cooperative Medical System collapsed alongside communal farming at the end of the Maoist period in 1976, leaving most farmers vulnerable[1]. In rural areas, where 80% of people have been without health insurance of any kind, illness has emerged as a leading cause of poverty[24]. To address the poor state of health care among the rural population, in 2003 the Chinese government launched the New Rural Cooperative Medical System （NCMS）,展开更多
We conduct questionnaire survey of migrant workers in Wenjiang District and Jintang County of Chengdu City,respectively,using the method of key-point investigation and the sampling survey.We describe the status quo of...We conduct questionnaire survey of migrant workers in Wenjiang District and Jintang County of Chengdu City,respectively,using the method of key-point investigation and the sampling survey.We describe the status quo of the sample migrant workers'participation in the New Rural Cooperative Medical System,analyze the issues concerning migrant workers'participation in the New Rural Cooperative Medical System,and put forward the countermeasures and recommendations as follows:using many types of medical insurance;establishing universal reimbursement points in strange land and premium-paying system for migrant workers;making the proportion of reimbursement open and transparent;establishing and improving medicare security system for migrant workers.展开更多
The new rural cooperative medical system has achieved periodical achievements since its establishment.Nevertheless,there are many factors hampering the development of the new system,such as the high cost,the difficult...The new rural cooperative medical system has achieved periodical achievements since its establishment.Nevertheless,there are many factors hampering the development of the new system,such as the high cost,the difficulties in fund procurement,the lack of management,the narrow coverage of benefit,the ineffective constraint to the designated medical institutions,the high fund balance rate,and the poor medical facilities and services in rural areas.Countermeasures are put forward to solve these problems,including improving the system design,expanding the coverage of the system,expanding the fund sources,reducing the financing costs,strengthening the fund supervision,enhancing the supervision of designated medical institutions,and improving the capacity of health services in rural areas.展开更多
A smart medical service system architecture is proposed in this paper to increase medical resource utilization and improve the efficiency of the medical diagnosis process for complex business scenarios in the Medical ...A smart medical service system architecture is proposed in this paper to increase medical resource utilization and improve the efficiency of the medical diagnosis process for complex business scenarios in the Medical Internet of Things(MIoT)environment.The resource representation model theory,multi-terminal aggregation algorithm,and the resource discovery algorithm based on latent factor model are also studied.A smart medical service system within the IoT environment is then developed,based on the open source project.Experimental results using real-world datasets illustrate that the proposed smart medical service system architecture can promote the intelligent and efficient management of medical resources to an extent,and assists in the develop towards digitization,intelligence,and precision in the field of medicine.展开更多
Hainan is an island province in south China with a high frequency of unconventional emergencies due to its special geographic location and national military defense role.Given the limited transportation route from Hai...Hainan is an island province in south China with a high frequency of unconventional emergencies due to its special geographic location and national military defense role.Given the limited transportation route from Hainan to the outside world,self-rescue is more important to Hainan Province than other provinces in China and it is therefore imperative to establish an independent, scientific as well as efficient provincal disaster medical system in Hainan.The regulatory role for vulnerability analysis/assessment has been demonstrated in establisment of disaster medical system in varoius countries and or regions.In this paper,we attempt to describe/propose how to adopt vulnerability assessment through mathematical modeling of major biophysical social vulnerability factors to establish an independent,scientific,effieicnt and comprehensive provincial disaster medical system in Hainan.展开更多
The purpose of hierarchical medical system is to lead in terms of improving efficiency, differentiating healthcare services and promoting labor division by changing the healthcare seeking behavior. The purpose of this...The purpose of hierarchical medical system is to lead in terms of improving efficiency, differentiating healthcare services and promoting labor division by changing the healthcare seeking behavior. The purpose of this research aims to discuss the public awareness of hierarchical medical system in Taiwan for the reference of health policy makers. We obtained our research data using a questionnaire survey;the total number of qualified patients was 1340. This research finds that more subjects agreed to the hierarchical medical system and medical referral system, but many people still disagreed with changes to their healthcare seeking choices due to policy promotion. Subtle changes, therefore, are observed that imply a crisis in terms of the trust in healthcare. The healthcare seeking behavior will not change if there is a difference between the medical awareness of patients and policy implementation, and the government needs to be concerned with this result when making policies.展开更多
The high tech industrial revolution in the last fifty years depleted and ruined the planet natural resources. Energy harvesting is the main challenge in the research in green technologies. Compact wideband efficient a...The high tech industrial revolution in the last fifty years depleted and ruined the planet natural resources. Energy harvesting is the main challenge in the research in green technologies. Compact wideband efficient antennas are crucial for energy harvesting portable sensors and systems. Small antennas have low efficiency. The efficiency of 5G, IoT communication and energy harvesting systems may be improved by using wideband efficient passive and active antennas. The system dynamic range may be improved by connecting amplifiers to the small antenna feed line. Ultra-wideband portable harvesting systems are presented in this paper. This paper presents new Ultra-Wideband energy harvesting system and antennas in frequencies ranging from 0.15 GHz to 18 GHz. Three wideband antennas cover the frequency range from 0.15 GHz to 18 GHz. A wideband metamaterial antenna with metallic strips covers the frequency range from 0.15 GHz to 0.42 GHz. The antenna bandwidth is around 75% for VSWR better than 2.3:1. A wideband slot antenna covers the frequency range from 0.4 GHz to 6.4 GHz. A wideband fractal notch antenna covers the frequency range from 6 GHz to 18 GHz. Printed passive and active notch and slot antennas are compact, low cost and have low volume. The active antennas may be employed in energy harvesting portable systems. The antennas and the harvesting system components may be assembled on the same, printed board. The printed notch and slot antennas bandwidth are from 75% to 100% for VSWR better than 3:1. The slot and notch antenna gain is around 3 dBi with efficiency higher than 90%. The antennas electrical parameters were computed in free space and near the human body. There is a good agreement between computed and measured results.展开更多
Our country rural area has carried out broad practice on new model system of rural cooperative medical services, and the rural new medical treatment system has developed quickly. However, there are still many problems...Our country rural area has carried out broad practice on new model system of rural cooperative medical services, and the rural new medical treatment system has developed quickly. However, there are still many problems which needs us to solve. This article will analysis its present situation, problems and reasons, then give some suggestions to solve these problems. The new rural cooperative medical system has made great achievements since its implementation, which is a radical reform of the traditional medical systen. Lcd by thc govcmmcnt, trying to solve the majority of the Chinese population of the peasant groups to see the doctor difficult and expensive medical problems, and effectively protect the vital interests of farmers, so that people=oriented, establish and improve the rural medical service system. This paper analyzes the status quo of the new rural cooperative medical system, puts forward the problems, finds the reasons, and puts forward the corresponding countermeasures on the basis of this.展开更多
Objectives This study aimed to design and evaluate a detection system for the accidental dislodgement of head-and-neck medical supplies through hand position recognition and tracking in Intensive Care Unit(ICU)patient...Objectives This study aimed to design and evaluate a detection system for the accidental dislodgement of head-and-neck medical supplies through hand position recognition and tracking in Intensive Care Unit(ICU)patients.Methods We conducted a single-center,prospective,parallel-group feasibility randomized controlled trial.We recruited 80 participants using convenience sampling from the ICU of a hospital in Ningbo City,Zhejiang Province,between March 2025 and June 2025,and they were randomly assigned to either the control group(routine care)or the intervention group(routine care plus image recognition-based detection system).The system continuously tracked patients’hand positions via bedside cameras and generated real-time alarms when hands entered predefined risk zones,notifying on-duty nurses to enable early intervention.System stability was assessed by continuous system uptime;system performance and clinical feasibility were evaluated by the frequencies of risk actions and accidental dislodgement of medical supplies(ADMS).Results All 80 participants completed the intervention,with 40 patients in each group.The baseline characteristics and median observation time of the two groups were balanced(intervention group:48 h/patient vs.control group:49 h/patient).Compared with the control group,the intervention group showed fewer ADMS(2/40 vs.9/40)and detected more risk actions per 100 h(36 vs.25);all system-detected events had corroborating images with complete concordance on manual review,and all nurse-recorded hand-contact events were accurately captured.Conclusions The study demonstrated that the image recognition-based detection system can function stably in clinical settings,providing accurate and continuous surveillance while supporting the early detection of risk actions.By reducing the observation burden and offering real-time cognitive support,the system complements routine nursing care and serves as an additional safety measure in ICU practice.With further optimization and larger multicenter validation,this approach could have the potential to make a significant contribution to the development of smart ICUs and the broader digital transformation of nursing care.展开更多
WITH the rapid development of technologies such as Artificial Intelligence(AI),edge computing,and cloud intelligence,the medical field is undergoing a fundamental transformation[1].These technologies significantly enh...WITH the rapid development of technologies such as Artificial Intelligence(AI),edge computing,and cloud intelligence,the medical field is undergoing a fundamental transformation[1].These technologies significantly enhance the medical system's capability to process complex data and also improve the real-time response rate to patient needs.In this wave of technological innovation,parallel intelligence,along with Artificial systems,Computational experiments,and Parallel execution(ACP)approach[2]will play a crucial role.Through parallel interactions between virtual and real systems,this approach optimizes the functionality of medical devices and instruments,enhancing the accuracy of diagnoses and treatments while enabling the autonomous evolution and adaptive adjustment of medical systems.展开更多
Background:Well-designed and functioning emergency medical service(EMS)can provide equitable access to emergency care to im-prove health issues,especially in low-and middle-income countries where the majority of death...Background:Well-designed and functioning emergency medical service(EMS)can provide equitable access to emergency care to im-prove health issues,especially in low-and middle-income countries where the majority of deaths are due to conditions that could be treated with emergency care.To address this gap,this study explored the contextually appropriate development process in addition to the system architecture,which is lacking in Global South EMS research.Method:This study was a thematic analysis of the development of EMS systems in six Asian countries.Experts in emergency care were selected through convenience sampling.Each country described and evaluated its EMS system using a standardized form with 102 EMS items that cover the emergency care system in terms of leadership,governance,financing,community-based activities,prehospital care,and quality assessment.From the descriptions,various themes were extracted focusing on the developmental perspective of EMS in Asia.Result:The study identified the domain of the developmental focus,best practices,and future strategies for EMS in the Asian region.The identified areas for developmental focus are governance,multidisciplinary collaboration,communication/coordination,community partic-ipation,decentralization,equitable access,supply-demand balance,and quality assurance activities.Conclusion:Countries under investigation achieved progress in planning,implementing,and sustaining EMS through varied strategies in the mentioned focal areas that can be emulated by other countries in this region.Further,their development levels varied according to the extent to which each country realized the development principles identified in this study.展开更多
The 21st-century global health landscape presents unprecedented challenges,such as antimicrobial resistance,mental health issues,and the rapid spread of infectious diseases due to urbanization and mobility.The Sendai ...The 21st-century global health landscape presents unprecedented challenges,such as antimicrobial resistance,mental health issues,and the rapid spread of infectious diseases due to urbanization and mobility.The Sendai Framework and initiatives such as Singapore’s analytics in combating dengue exemplify the push for disaster risk reduction and advanced preparedness.The recent pandemic has underscored the vulnerabilities of health systems,highlighting the need for telehealth and improved emergency response capacities.Military-civilian partner-ships and psychological support for healthcare workers have emerged as some critical components.Embracing an all-hazard approach and prioritizing environmental and psychological resilience are key to a robust,culturally sensitive global health strategy,emphasizing the im-portance of open-access research for comprehensive global preparedness.展开更多
【Objective】Medical imaging data has great value,but it contains a significant amount of sensitive information about patients.At present,laws and regulations regarding to the de-identification of medical imaging data...【Objective】Medical imaging data has great value,but it contains a significant amount of sensitive information about patients.At present,laws and regulations regarding to the de-identification of medical imaging data are not clearly defined around the world.This study aims to develop a tool that meets compliance-driven desensitization requirements tailored to diverse research needs.【Methods】To enhance the security of medical image data,we designed and implemented a DICOM format medical image de-identification system on the Windows operating system.【Results】Our custom de-identification system is adaptable to the legal standards of different countries and can accommodate specific research demands.The system offers both web-based online and desktop offline de-identification capabilities,enabling customization of de-identification rules and facilitating batch processing to improve efficiency.【Conclusions】This medical image de-identification system robustly strengthens the stewardship of sensitive medical data,aligning with data security protection requirements while facilitating the sharing and utilization of medical image data.This approach unlocks the intrinsic value inherent in such datasets.展开更多
The rapid advancement of artificial intelligence(AI)has ushered in a new era of medical multimodal large language models(MLLMs),which integrate diverse data modalities such as text,imaging,physiological signals,and ge...The rapid advancement of artificial intelligence(AI)has ushered in a new era of medical multimodal large language models(MLLMs),which integrate diverse data modalities such as text,imaging,physiological signals,and genomics to enhance clinical decision-making.This systematic review explores the core methodologies and applied research frontiers of medical MLLMs,focusing on their architecture,training methods,evaluation techniques,and applications.We highlight the transformative potential of MLLMs in achieving cross-modal semantic alignment,medical knowledge integration,and robust clinical reasoning.Despite their promise,challenges such as data heterogeneity,hallucination,and computational efficiency persist.By reviewing state-of-the-art solutions and future directions,this paper provides a comprehensive technical guide for developing reliable and interpretable medical MLLMs,ultimately aiming to bridge the gap between AI and clinical practice.展开更多
Objective: To identify the principal factors associated with the occurrence and development of medical device-related pressure injuries (MDRPI) in adults admitted to hospitals. MDRPI, a peculiar subtype of pressure in...Objective: To identify the principal factors associated with the occurrence and development of medical device-related pressure injuries (MDRPI) in adults admitted to hospitals. MDRPI, a peculiar subtype of pressure injuries (PI), result from the pression exerted by devices (or their fixation systems) applied for diagnostic and therapeutic purposes. MDRPI represent a serious problem for patients and healthcare systems. Understanding potential risk factors is an important step in implementing effective interventions. Methods: In this study, we will perform a systematic review;if possible, also a meta-analysis will be performed. The review will follow the preferred reporting items for systematic reviews and meta-analyses (PRISMA) reporting guidelines for systematic reviews. A rigorous literature search will be conducted both in electronic databases (Medline/PubMed, Embase, CINAHL, Web of Science, Scopus, Cochrane Library) to identify studies published since 2000 and in gray literature for unpublished studies. Pairs of researchers will identify relevant evidence, extract data, and assess risk of bias independently in each eligible study. Factors associated with the occurrence of MDRPI are considered the primary outcome. Secondary outcomes are prevalence and incidence of MDRPI, length of hospital stay, infections, and death. The evidence will be synthesized using the GRADE methodology. Results: Results are not currently available as this is a protocol for a systematic review. Conclusions: This systematic review will identify evidence on risk factors for developing MDRPI. We are confident that the results of this review will help to improve clinical practice and guide future research.展开更多
The YOLO(You Only Look Once)series,a leading single-stage object detection framework,has gained significant prominence in medical-image analysis due to its real-time efficiency and robust performance.Recent iterations...The YOLO(You Only Look Once)series,a leading single-stage object detection framework,has gained significant prominence in medical-image analysis due to its real-time efficiency and robust performance.Recent iterations of YOLO have further enhanced its accuracy and reliability in critical clinical tasks such as tumor detection,lesion segmentation,and microscopic image analysis,thereby accelerating the development of clinical decision support systems.This paper systematically reviews advances in YOLO-based medical object detection from 2018 to 2024.It compares YOLO’s performance with othermodels(e.g.,Faster R-CNN,RetinaNet)inmedical contexts,summarizes standard evaluation metrics(e.g.,mean Average Precision(mAP),sensitivity),and analyzes hardware deployment strategies using public datasets such as LUNA16,BraTS,andCheXpert.Thereviewhighlights the impressive performance of YOLO models,particularly from YOLOv5 to YOLOv8,in achieving high precision(up to 99.17%),sensitivity(up to 97.5%),and mAP exceeding 95%in tasks such as lung nodule,breast cancer,and polyp detection.These results demonstrate the significant potential of YOLO models for early disease detection and real-time clinical applications,indicating their ability to enhance clinical workflows.However,the study also identifies key challenges,including high small-object miss rates,limited generalization in low-contrast images,scarcity of annotated data,and model interpretability issues.Finally,the potential future research directions are also proposed to address these challenges and further advance the application of YOLO models in healthcare.展开更多
With the continuous advancement of the tiered diagnosis and treatment system,the medical consortium model has gained increasing attention as an important approach to promoting the vertical integration of healthcare re...With the continuous advancement of the tiered diagnosis and treatment system,the medical consortium model has gained increasing attention as an important approach to promoting the vertical integration of healthcare resources.Within this context,laboratory data,as a key component of healthcare information systems,urgently requires efficient sharing and intelligent analysis.This paper designs and constructs an intelligent early warning system for laboratory data based on a cloud platform tailored to the medical consortium model.Through standardized data formats and unified access interfaces,the system enables the integration and cleaning of laboratory data across multiple healthcare institutions.By combining medical rule sets with machine learning models,the system achieves graded alerts and rapid responses to abnormal key indicators and potential outbreaks of infectious diseases.Practical deployment results demonstrate that the system significantly improves the utilization efficiency of laboratory data,strengthens public health event monitoring,and optimizes inter-institutional collaboration.The paper also discusses challenges encountered during system implementation,such as inconsistent data standards,security and compliance concerns,and model interpretability,and proposes corresponding optimization strategies.These findings provide a reference for the broader application of intelligent medical early warning systems.展开更多
Feature selection(FS)plays a crucial role in medical imaging by reducing dimensionality,improving computational efficiency,and enhancing diagnostic accuracy.Traditional FS techniques,including filter,wrapper,and embed...Feature selection(FS)plays a crucial role in medical imaging by reducing dimensionality,improving computational efficiency,and enhancing diagnostic accuracy.Traditional FS techniques,including filter,wrapper,and embedded methods,have been widely used but often struggle with high-dimensional and heterogeneous medical imaging data.Deep learning-based FS methods,particularly Convolutional Neural Networks(CNNs)and autoencoders,have demonstrated superior performance but lack interpretability.Hybrid approaches that combine classical and deep learning techniques have emerged as a promising solution,offering improved accuracy and explainability.Furthermore,integratingmulti-modal imaging data(e.g.,MagneticResonance Imaging(MRI),ComputedTomography(CT),Positron Emission Tomography(PET),and Ultrasound(US))poses additional challenges in FS,necessitating advanced feature fusion strategies.Multi-modal feature fusion combines information fromdifferent imagingmodalities to improve diagnostic accuracy.Recently,quantum computing has gained attention as a revolutionary approach for FS,providing the potential to handle high-dimensional medical data more efficiently.This systematic literature review comprehensively examines classical,Deep Learning(DL),hybrid,and quantum-based FS techniques inmedical imaging.Key outcomes include a structured taxonomy of FS methods,a critical evaluation of their performance across modalities,and identification of core challenges such as computational burden,interpretability,and ethical considerations.Future research directions—such as explainable AI(XAI),federated learning,and quantum-enhanced FS—are also emphasized to bridge the current gaps.This review provides actionable insights for developing scalable,interpretable,and clinically applicable FS methods in the evolving landscape of medical imaging.展开更多
Secure and automated sharing of medical information among different medical entities/stakeholders like patients,hospitals,doctors,law enforcement agencies,health insurance companies etc.,in a standard format has alway...Secure and automated sharing of medical information among different medical entities/stakeholders like patients,hospitals,doctors,law enforcement agencies,health insurance companies etc.,in a standard format has always been a challenging problem.Current methods for ensuring compliance with medical privacy laws require specialists who are deeply familiar with these laws'complex requirements to verify the lawful exchange of medical information.This article introduces a Smart Medical Data Exchange Engine(SDEE)designed to automate the extracting of logical rules from medical privacy legislation using advanced techniques.These rules facilitate the secure extraction of information,safeguarding patient privacy and confidentiality.In addition,SMDEE can generate standardised clinical documents according to Health Level 7(HL7)standards and also standardise the nomenclature of requested medical data,enabling accurate decision-making when accessing patient data.All access requests to patient information are processed through SMDEE to ensure authorised access.The proposed system's efficacy is evaluated using the Health Insurance Portability and Accountability Act(HIPAA),a fundamental privacy law in the United States.However,SMDEE's flexibility allows its application worldwide,accommodating various medical privacy laws.Beyond facilitating global information exchange,SMDEE aims to enhance international patients'timely and appropriate treatment.展开更多
文摘This paper explores increased use of the concept of“medical bilingualism”since 2015 as scholars,especially of East Asian medical history and anthropology,have applied it to engagements between two medical systems.It reveals an ongoing evolution in the way that scholars understand what a medical system is and how medical systems are differentiated and compared with one another.The image of culturally homogeneous systems of meaning and practice that dominated mid-twentieth-century scholarship on medical systems(especially using the category of ethnomedicines)has been giving way to a more culturally heterogeneous and cosmopolitan picture of how medical practitioners evolve,integrate,and differentiate medical concepts and practices in the context of contemporary societies and the new forms of life they engender.This reformulated concept of medical bilingualism emphasizes the ways in which medical systems overlap yet remain distinct.First,the paper summarizes results of an experiment with AI searches on medical bilingualism,then narrates its historiography both pre-COVID-19 and during COVID-19,and finally concludes with some reflections on language ideology,multilingualism,and medical pluralism.
文摘China＇s Rural Cooperative Medical System collapsed alongside communal farming at the end of the Maoist period in 1976, leaving most farmers vulnerable[1]. In rural areas, where 80% of people have been without health insurance of any kind, illness has emerged as a leading cause of poverty[24]. To address the poor state of health care among the rural population, in 2003 the Chinese government launched the New Rural Cooperative Medical System （NCMS）,
文摘We conduct questionnaire survey of migrant workers in Wenjiang District and Jintang County of Chengdu City,respectively,using the method of key-point investigation and the sampling survey.We describe the status quo of the sample migrant workers'participation in the New Rural Cooperative Medical System,analyze the issues concerning migrant workers'participation in the New Rural Cooperative Medical System,and put forward the countermeasures and recommendations as follows:using many types of medical insurance;establishing universal reimbursement points in strange land and premium-paying system for migrant workers;making the proportion of reimbursement open and transparent;establishing and improving medicare security system for migrant workers.
基金Supported by the School Management Project of Xi an Polytechnic University(09XG38)
文摘The new rural cooperative medical system has achieved periodical achievements since its establishment.Nevertheless,there are many factors hampering the development of the new system,such as the high cost,the difficulties in fund procurement,the lack of management,the narrow coverage of benefit,the ineffective constraint to the designated medical institutions,the high fund balance rate,and the poor medical facilities and services in rural areas.Countermeasures are put forward to solve these problems,including improving the system design,expanding the coverage of the system,expanding the fund sources,reducing the financing costs,strengthening the fund supervision,enhancing the supervision of designated medical institutions,and improving the capacity of health services in rural areas.
基金supported by the National Key R&D Program of China(2018YFC1314901)the Natural Science Foundation of China (61871446)the Scientific Research Starting Foundation for New Teachers of Nanjing University of Posts and Telecommunications (NY217033)
文摘A smart medical service system architecture is proposed in this paper to increase medical resource utilization and improve the efficiency of the medical diagnosis process for complex business scenarios in the Medical Internet of Things(MIoT)environment.The resource representation model theory,multi-terminal aggregation algorithm,and the resource discovery algorithm based on latent factor model are also studied.A smart medical service system within the IoT environment is then developed,based on the open source project.Experimental results using real-world datasets illustrate that the proposed smart medical service system architecture can promote the intelligent and efficient management of medical resources to an extent,and assists in the develop towards digitization,intelligence,and precision in the field of medicine.
基金supported by 2010 Natural Science foundation of China(81060160)2008 Natural Science Foundation of China(30860082)+1 种基金2009 Natural Science Foundation of China(090209)2010 Key Scientific and Technological Project of Hainan Province(zdxm20100043)
文摘Hainan is an island province in south China with a high frequency of unconventional emergencies due to its special geographic location and national military defense role.Given the limited transportation route from Hainan to the outside world,self-rescue is more important to Hainan Province than other provinces in China and it is therefore imperative to establish an independent, scientific as well as efficient provincal disaster medical system in Hainan.The regulatory role for vulnerability analysis/assessment has been demonstrated in establisment of disaster medical system in varoius countries and or regions.In this paper,we attempt to describe/propose how to adopt vulnerability assessment through mathematical modeling of major biophysical social vulnerability factors to establish an independent,scientific,effieicnt and comprehensive provincial disaster medical system in Hainan.
文摘The purpose of hierarchical medical system is to lead in terms of improving efficiency, differentiating healthcare services and promoting labor division by changing the healthcare seeking behavior. The purpose of this research aims to discuss the public awareness of hierarchical medical system in Taiwan for the reference of health policy makers. We obtained our research data using a questionnaire survey;the total number of qualified patients was 1340. This research finds that more subjects agreed to the hierarchical medical system and medical referral system, but many people still disagreed with changes to their healthcare seeking choices due to policy promotion. Subtle changes, therefore, are observed that imply a crisis in terms of the trust in healthcare. The healthcare seeking behavior will not change if there is a difference between the medical awareness of patients and policy implementation, and the government needs to be concerned with this result when making policies.
文摘The high tech industrial revolution in the last fifty years depleted and ruined the planet natural resources. Energy harvesting is the main challenge in the research in green technologies. Compact wideband efficient antennas are crucial for energy harvesting portable sensors and systems. Small antennas have low efficiency. The efficiency of 5G, IoT communication and energy harvesting systems may be improved by using wideband efficient passive and active antennas. The system dynamic range may be improved by connecting amplifiers to the small antenna feed line. Ultra-wideband portable harvesting systems are presented in this paper. This paper presents new Ultra-Wideband energy harvesting system and antennas in frequencies ranging from 0.15 GHz to 18 GHz. Three wideband antennas cover the frequency range from 0.15 GHz to 18 GHz. A wideband metamaterial antenna with metallic strips covers the frequency range from 0.15 GHz to 0.42 GHz. The antenna bandwidth is around 75% for VSWR better than 2.3:1. A wideband slot antenna covers the frequency range from 0.4 GHz to 6.4 GHz. A wideband fractal notch antenna covers the frequency range from 6 GHz to 18 GHz. Printed passive and active notch and slot antennas are compact, low cost and have low volume. The active antennas may be employed in energy harvesting portable systems. The antennas and the harvesting system components may be assembled on the same, printed board. The printed notch and slot antennas bandwidth are from 75% to 100% for VSWR better than 3:1. The slot and notch antenna gain is around 3 dBi with efficiency higher than 90%. The antennas electrical parameters were computed in free space and near the human body. There is a good agreement between computed and measured results.
文摘Our country rural area has carried out broad practice on new model system of rural cooperative medical services, and the rural new medical treatment system has developed quickly. However, there are still many problems which needs us to solve. This article will analysis its present situation, problems and reasons, then give some suggestions to solve these problems. The new rural cooperative medical system has made great achievements since its implementation, which is a radical reform of the traditional medical systen. Lcd by thc govcmmcnt, trying to solve the majority of the Chinese population of the peasant groups to see the doctor difficult and expensive medical problems, and effectively protect the vital interests of farmers, so that people=oriented, establish and improve the rural medical service system. This paper analyzes the status quo of the new rural cooperative medical system, puts forward the problems, finds the reasons, and puts forward the corresponding countermeasures on the basis of this.
文摘Objectives This study aimed to design and evaluate a detection system for the accidental dislodgement of head-and-neck medical supplies through hand position recognition and tracking in Intensive Care Unit(ICU)patients.Methods We conducted a single-center,prospective,parallel-group feasibility randomized controlled trial.We recruited 80 participants using convenience sampling from the ICU of a hospital in Ningbo City,Zhejiang Province,between March 2025 and June 2025,and they were randomly assigned to either the control group(routine care)or the intervention group(routine care plus image recognition-based detection system).The system continuously tracked patients’hand positions via bedside cameras and generated real-time alarms when hands entered predefined risk zones,notifying on-duty nurses to enable early intervention.System stability was assessed by continuous system uptime;system performance and clinical feasibility were evaluated by the frequencies of risk actions and accidental dislodgement of medical supplies(ADMS).Results All 80 participants completed the intervention,with 40 patients in each group.The baseline characteristics and median observation time of the two groups were balanced(intervention group:48 h/patient vs.control group:49 h/patient).Compared with the control group,the intervention group showed fewer ADMS(2/40 vs.9/40)and detected more risk actions per 100 h(36 vs.25);all system-detected events had corroborating images with complete concordance on manual review,and all nurse-recorded hand-contact events were accurately captured.Conclusions The study demonstrated that the image recognition-based detection system can function stably in clinical settings,providing accurate and continuous surveillance while supporting the early detection of risk actions.By reducing the observation burden and offering real-time cognitive support,the system complements routine nursing care and serves as an additional safety measure in ICU practice.With further optimization and larger multicenter validation,this approach could have the potential to make a significant contribution to the development of smart ICUs and the broader digital transformation of nursing care.
基金supported by the Science and Technology Development Fund,Macao Special Administrative Region(SAR)(0093/2023/RIA2,0145/2023/RIA3).
文摘WITH the rapid development of technologies such as Artificial Intelligence(AI),edge computing,and cloud intelligence,the medical field is undergoing a fundamental transformation[1].These technologies significantly enhance the medical system's capability to process complex data and also improve the real-time response rate to patient needs.In this wave of technological innovation,parallel intelligence,along with Artificial systems,Computational experiments,and Parallel execution(ACP)approach[2]will play a crucial role.Through parallel interactions between virtual and real systems,this approach optimizes the functionality of medical devices and instruments,enhancing the accuracy of diagnoses and treatments while enabling the autonomous evolution and adaptive adjustment of medical systems.
基金supported by the Japan Society for the Promotion of Science KAKENHI(19 K09403)the funding body did not play any role in the study or preparation of the manuscript.
文摘Background:Well-designed and functioning emergency medical service(EMS)can provide equitable access to emergency care to im-prove health issues,especially in low-and middle-income countries where the majority of deaths are due to conditions that could be treated with emergency care.To address this gap,this study explored the contextually appropriate development process in addition to the system architecture,which is lacking in Global South EMS research.Method:This study was a thematic analysis of the development of EMS systems in six Asian countries.Experts in emergency care were selected through convenience sampling.Each country described and evaluated its EMS system using a standardized form with 102 EMS items that cover the emergency care system in terms of leadership,governance,financing,community-based activities,prehospital care,and quality assessment.From the descriptions,various themes were extracted focusing on the developmental perspective of EMS in Asia.Result:The study identified the domain of the developmental focus,best practices,and future strategies for EMS in the Asian region.The identified areas for developmental focus are governance,multidisciplinary collaboration,communication/coordination,community partic-ipation,decentralization,equitable access,supply-demand balance,and quality assurance activities.Conclusion:Countries under investigation achieved progress in planning,implementing,and sustaining EMS through varied strategies in the mentioned focal areas that can be emulated by other countries in this region.Further,their development levels varied according to the extent to which each country realized the development principles identified in this study.
文摘The 21st-century global health landscape presents unprecedented challenges,such as antimicrobial resistance,mental health issues,and the rapid spread of infectious diseases due to urbanization and mobility.The Sendai Framework and initiatives such as Singapore’s analytics in combating dengue exemplify the push for disaster risk reduction and advanced preparedness.The recent pandemic has underscored the vulnerabilities of health systems,highlighting the need for telehealth and improved emergency response capacities.Military-civilian partner-ships and psychological support for healthcare workers have emerged as some critical components.Embracing an all-hazard approach and prioritizing environmental and psychological resilience are key to a robust,culturally sensitive global health strategy,emphasizing the im-portance of open-access research for comprehensive global preparedness.
基金CAMS Innovation Fund for Medical Sciences(CIFMS):“Construction of an Intelligent Management and Efficient Utilization Technology System for Big Data in Population Health Science.”(2021-I2M-1-057)Key Projects of the Innovation Fund of the National Clinical Research Center for Orthopedics and Sports Rehabilitation:“National Orthopedics and Sports Rehabilitation Real-World Research Platform System Construction”(23-NCRC-CXJJ-ZD4)。
文摘【Objective】Medical imaging data has great value,but it contains a significant amount of sensitive information about patients.At present,laws and regulations regarding to the de-identification of medical imaging data are not clearly defined around the world.This study aims to develop a tool that meets compliance-driven desensitization requirements tailored to diverse research needs.【Methods】To enhance the security of medical image data,we designed and implemented a DICOM format medical image de-identification system on the Windows operating system.【Results】Our custom de-identification system is adaptable to the legal standards of different countries and can accommodate specific research demands.The system offers both web-based online and desktop offline de-identification capabilities,enabling customization of de-identification rules and facilitating batch processing to improve efficiency.【Conclusions】This medical image de-identification system robustly strengthens the stewardship of sensitive medical data,aligning with data security protection requirements while facilitating the sharing and utilization of medical image data.This approach unlocks the intrinsic value inherent in such datasets.
基金supported by the National Natural Science Foundation of China(Grant No.:62172458).
文摘The rapid advancement of artificial intelligence(AI)has ushered in a new era of medical multimodal large language models(MLLMs),which integrate diverse data modalities such as text,imaging,physiological signals,and genomics to enhance clinical decision-making.This systematic review explores the core methodologies and applied research frontiers of medical MLLMs,focusing on their architecture,training methods,evaluation techniques,and applications.We highlight the transformative potential of MLLMs in achieving cross-modal semantic alignment,medical knowledge integration,and robust clinical reasoning.Despite their promise,challenges such as data heterogeneity,hallucination,and computational efficiency persist.By reviewing state-of-the-art solutions and future directions,this paper provides a comprehensive technical guide for developing reliable and interpretable medical MLLMs,ultimately aiming to bridge the gap between AI and clinical practice.
文摘Objective: To identify the principal factors associated with the occurrence and development of medical device-related pressure injuries (MDRPI) in adults admitted to hospitals. MDRPI, a peculiar subtype of pressure injuries (PI), result from the pression exerted by devices (or their fixation systems) applied for diagnostic and therapeutic purposes. MDRPI represent a serious problem for patients and healthcare systems. Understanding potential risk factors is an important step in implementing effective interventions. Methods: In this study, we will perform a systematic review;if possible, also a meta-analysis will be performed. The review will follow the preferred reporting items for systematic reviews and meta-analyses (PRISMA) reporting guidelines for systematic reviews. A rigorous literature search will be conducted both in electronic databases (Medline/PubMed, Embase, CINAHL, Web of Science, Scopus, Cochrane Library) to identify studies published since 2000 and in gray literature for unpublished studies. Pairs of researchers will identify relevant evidence, extract data, and assess risk of bias independently in each eligible study. Factors associated with the occurrence of MDRPI are considered the primary outcome. Secondary outcomes are prevalence and incidence of MDRPI, length of hospital stay, infections, and death. The evidence will be synthesized using the GRADE methodology. Results: Results are not currently available as this is a protocol for a systematic review. Conclusions: This systematic review will identify evidence on risk factors for developing MDRPI. We are confident that the results of this review will help to improve clinical practice and guide future research.
基金supported by the National Natural Science Foundation of China under grant number 62066016the Natural Science Foundation of Hunan Province of China under grant number 2024JJ7395+2 种基金the Scientific Research Project of Education Department of Hunan Province of China under grant number 22B0549International and Regional Science and Technology Cooperation and Exchange Program of the Hunan Association for Science and Technology under grant number 025SKX-KJ-04Hunan Province Undergraduate Innovation and Entrepreneurship Training Program(grant number S202410531015).
文摘The YOLO(You Only Look Once)series,a leading single-stage object detection framework,has gained significant prominence in medical-image analysis due to its real-time efficiency and robust performance.Recent iterations of YOLO have further enhanced its accuracy and reliability in critical clinical tasks such as tumor detection,lesion segmentation,and microscopic image analysis,thereby accelerating the development of clinical decision support systems.This paper systematically reviews advances in YOLO-based medical object detection from 2018 to 2024.It compares YOLO’s performance with othermodels(e.g.,Faster R-CNN,RetinaNet)inmedical contexts,summarizes standard evaluation metrics(e.g.,mean Average Precision(mAP),sensitivity),and analyzes hardware deployment strategies using public datasets such as LUNA16,BraTS,andCheXpert.Thereviewhighlights the impressive performance of YOLO models,particularly from YOLOv5 to YOLOv8,in achieving high precision(up to 99.17%),sensitivity(up to 97.5%),and mAP exceeding 95%in tasks such as lung nodule,breast cancer,and polyp detection.These results demonstrate the significant potential of YOLO models for early disease detection and real-time clinical applications,indicating their ability to enhance clinical workflows.However,the study also identifies key challenges,including high small-object miss rates,limited generalization in low-contrast images,scarcity of annotated data,and model interpretability issues.Finally,the potential future research directions are also proposed to address these challenges and further advance the application of YOLO models in healthcare.
文摘With the continuous advancement of the tiered diagnosis and treatment system,the medical consortium model has gained increasing attention as an important approach to promoting the vertical integration of healthcare resources.Within this context,laboratory data,as a key component of healthcare information systems,urgently requires efficient sharing and intelligent analysis.This paper designs and constructs an intelligent early warning system for laboratory data based on a cloud platform tailored to the medical consortium model.Through standardized data formats and unified access interfaces,the system enables the integration and cleaning of laboratory data across multiple healthcare institutions.By combining medical rule sets with machine learning models,the system achieves graded alerts and rapid responses to abnormal key indicators and potential outbreaks of infectious diseases.Practical deployment results demonstrate that the system significantly improves the utilization efficiency of laboratory data,strengthens public health event monitoring,and optimizes inter-institutional collaboration.The paper also discusses challenges encountered during system implementation,such as inconsistent data standards,security and compliance concerns,and model interpretability,and proposes corresponding optimization strategies.These findings provide a reference for the broader application of intelligent medical early warning systems.
文摘Feature selection(FS)plays a crucial role in medical imaging by reducing dimensionality,improving computational efficiency,and enhancing diagnostic accuracy.Traditional FS techniques,including filter,wrapper,and embedded methods,have been widely used but often struggle with high-dimensional and heterogeneous medical imaging data.Deep learning-based FS methods,particularly Convolutional Neural Networks(CNNs)and autoencoders,have demonstrated superior performance but lack interpretability.Hybrid approaches that combine classical and deep learning techniques have emerged as a promising solution,offering improved accuracy and explainability.Furthermore,integratingmulti-modal imaging data(e.g.,MagneticResonance Imaging(MRI),ComputedTomography(CT),Positron Emission Tomography(PET),and Ultrasound(US))poses additional challenges in FS,necessitating advanced feature fusion strategies.Multi-modal feature fusion combines information fromdifferent imagingmodalities to improve diagnostic accuracy.Recently,quantum computing has gained attention as a revolutionary approach for FS,providing the potential to handle high-dimensional medical data more efficiently.This systematic literature review comprehensively examines classical,Deep Learning(DL),hybrid,and quantum-based FS techniques inmedical imaging.Key outcomes include a structured taxonomy of FS methods,a critical evaluation of their performance across modalities,and identification of core challenges such as computational burden,interpretability,and ethical considerations.Future research directions—such as explainable AI(XAI),federated learning,and quantum-enhanced FS—are also emphasized to bridge the current gaps.This review provides actionable insights for developing scalable,interpretable,and clinically applicable FS methods in the evolving landscape of medical imaging.
基金fully supported by the University of Vaasa and VTT Technical Research Centre of Finland.
文摘Secure and automated sharing of medical information among different medical entities/stakeholders like patients,hospitals,doctors,law enforcement agencies,health insurance companies etc.,in a standard format has always been a challenging problem.Current methods for ensuring compliance with medical privacy laws require specialists who are deeply familiar with these laws'complex requirements to verify the lawful exchange of medical information.This article introduces a Smart Medical Data Exchange Engine(SDEE)designed to automate the extracting of logical rules from medical privacy legislation using advanced techniques.These rules facilitate the secure extraction of information,safeguarding patient privacy and confidentiality.In addition,SMDEE can generate standardised clinical documents according to Health Level 7(HL7)standards and also standardise the nomenclature of requested medical data,enabling accurate decision-making when accessing patient data.All access requests to patient information are processed through SMDEE to ensure authorised access.The proposed system's efficacy is evaluated using the Health Insurance Portability and Accountability Act(HIPAA),a fundamental privacy law in the United States.However,SMDEE's flexibility allows its application worldwide,accommodating various medical privacy laws.Beyond facilitating global information exchange,SMDEE aims to enhance international patients'timely and appropriate treatment.
