With gastric cancer ranking among the most prevalent and deadly malignancies worldwide,early detection and individualized prognosis remain essential for improving patient outcomes.This letter discusses recent advancem...With gastric cancer ranking among the most prevalent and deadly malignancies worldwide,early detection and individualized prognosis remain essential for improving patient outcomes.This letter discusses recent advancements in arti-ficial intelligence(AI)-driven predictive tools for gastric cancer,emphasizing a computed tomography-based radiomic model that achieved a predictive accuracy of area under the curve of 0.893 for treatment response in advanced cases undergoing neoadjuvant immunochemotherapy.AI offers promising avenues for predictive accuracy and personalized treatment planning in gastric oncology.Additionally,this letter highlights the comparison of these AI tools with tra-ditional methodologies,demonstrating their potential to streamline clinical workflows and address existing gaps in risk stratification and early detection.Furthermore,this letter addresses the ethical considerations and the need for robust clinical-AI collaboration to achieve reliable,transparent,and unbiased outcomes.Strengthening cross-disciplinary efforts will be vital for the responsible and effective deployment of AI in this critical area of oncology.展开更多
Embodied intelligence represents a new paradigm for the cross-integration development of artificial intelli⁃gence.By endowing AI with a"physical body",it enables interaction with the real world,allowing AI t...Embodied intelligence represents a new paradigm for the cross-integration development of artificial intelli⁃gence.By endowing AI with a"physical body",it enables interaction with the real world,allowing AI to move beyond digital environments into the physical realm and demonstrate intelligence that simulates or even surpasses human capa⁃bilities.Although embodied artificial intelligence demonstrates substantial potential in the realm of invention and cre⁃ation,there remain challenges in obtaining patent authorization for its generated technical solutions,specifically con⁃cerning subject,object,and market aspects.To address these issues,the feasibility of the subject should be demon⁃strated from the perspective of embodied cognition theory,while the object should be justified from a techno-centric standpoint.Subsequently,a regulatory framework for the patentability of technical solutions generated by embodied in⁃telligence should be proposed.First,a more inclusive subject framework should be established,recognizing embodied artificial intelligence as an inventor alongside humans,thereby affirming a coexistent"inventor"identity.Second,pat⁃ent rights should be assigned to developers of embodied artificial intelligence,referencing the rights distribution para⁃digm under employment relationships.Third,the criteria for patent eligibility and the"three-aspect"examination stan⁃dards should be refined.Finally,mechanisms for optimizing the implementation of rights and risk prevention should be developed.展开更多
Psychosomatic disorders,characterized by significant contributions of psychosocial factors to the pathogenesis and progression of somatic organic diseases or functional impairments(e.g.,diabetes,essential hypertension...Psychosomatic disorders,characterized by significant contributions of psychosocial factors to the pathogenesis and progression of somatic organic diseases or functional impairments(e.g.,diabetes,essential hypertension,asthma,inflammatory bowel disease,and neurodermatitis),present unique diagnostic and therapeutic challenges[1].Traditional diagnostic frameworks,heavily reliant on clinicians’subjective judgment and limited by the qualitative nature of psychological assessments,often result in misdiagnosis or delayed detection.As a cornerstone of the Fourth Industrial Revolution,artificial intelligence(AI)has demonstrated transformative potential in medicine.In psychosomatic medicine,AI leverages advanced data analytics,machine learning,and natural language processing to decipher the intricate interplay between psychological and physiological mechanisms,offering novel tools for diagnosis,treatment,and prevention.However,its clinical integration raises critical ethical and operational concerns that warrant rigorous examination.展开更多
Efficient working capital management(WCM)creates value for both management and shareholders by enhancing cash flows and reducing investment in receivables and inventory.It supports liquidity and minimizes financial di...Efficient working capital management(WCM)creates value for both management and shareholders by enhancing cash flows and reducing investment in receivables and inventory.It supports liquidity and minimizes financial distress risks,aligning with the goal of shareholder value maximization.However,traditional manual approaches to WCM are no longer sufficient due to the rapid and complex changes in economic and business environments.As a result,firms increasingly rely on artificial intelligence(AI)in WCM.AI offers advanced capabilities in prediction,monitoring,and problem-solving by processing vast data,identifying variable relationships,and adapting to change faster than human cognition.This paper explores the fundamentals of WCM and AI,their interconnections,and the strategic opportunities AI introduces to optimize WCM in modern enterprises.展开更多
This review comprehensively summarized the potential of artificial intelligence(AI)in the management of esophageal cancer.It highlighted the significance of AI-assisted endoscopy in Japan where endoscopy is central to...This review comprehensively summarized the potential of artificial intelligence(AI)in the management of esophageal cancer.It highlighted the significance of AI-assisted endoscopy in Japan where endoscopy is central to both screening and diagnosis.For the clinical adaptation of AI,several challenges remain for its effective translation.The establishment of high-quality clinical databases,such as the National Clinical Database and Japan Endoscopy Database in Japan,which covers almost all cases of esophageal cancer,is essential for validating multimodal AI models.This requires rigorous external validation using diverse datasets,including those from different endoscope manufacturers and image qualities.Furthermore,endoscopists’skills significantly affect diagnostic accuracy,suggesting that AI should serve as a supportive tool rather than a replacement.Addressing these challenges,along with country-specific legal and ethical considerations,will facilitate the successful integration of multimodal AI into the management of esophageal cancer,particularly in endoscopic diagnosis,and contribute to improved patient outcomes.Although this review focused on Japan as a case study,the challenges and solutions described are broadly applicable to other high-incidence regions.展开更多
Artificial intelligence(AI)is revolutionizing medical imaging,particularly in chronic liver diseases assessment.AI technologies,including machine learning and deep learning,are increasingly integrated with multiparame...Artificial intelligence(AI)is revolutionizing medical imaging,particularly in chronic liver diseases assessment.AI technologies,including machine learning and deep learning,are increasingly integrated with multiparametric ultrasound(US)techniques to provide more accurate,objective,and non-invasive evaluations of liver fibrosis and steatosis.Analyzing large datasets from US images,AI enhances diagnostic precision,enabling better quantification of liver stiffness and fat content,which are essential for diagnosing and staging liver fibrosis and steatosis.Combining advanced US modalities,such as elastography and doppler imaging with AI,has demonstrated improved sensitivity in identifying different stages of liver disease and distinguishing various degrees of steatotic liver.These advancements also contribute to greater reproducibility and reduced operator dependency,addressing some of the limitations of traditional methods.The clinical implications of AI in liver disease are vast,ranging from early detection to predicting disease progression and evaluating treatment response.Despite these promising developments,challenges such as the need for large-scale datasets,algorithm transparency,and clinical validation remain.The aim of this review is to explore the current applications and future potential of AI in liver fibrosis and steatosis assessment using multiparametric US,highlighting the technological advances and clinical relevance of this emerging field.展开更多
BACKGROUND Gastrointestinal stromal tumors(GISTs)are rare mesenchymal neoplasms primarily originating in the stomach or small intestine.Duodenal GISTs are particularly uncommon,accounting for only a small fraction of ...BACKGROUND Gastrointestinal stromal tumors(GISTs)are rare mesenchymal neoplasms primarily originating in the stomach or small intestine.Duodenal GISTs are particularly uncommon,accounting for only a small fraction of GIST cases.These tumors often present with nonspecific symptoms,making early detection challenging.This case discusses a duodenal GIST misdiagnosed as pancreatic cancer due to obstructive jaundice.CASE SUMMARY A 40-year-old male with jaundice and abdominal symptoms underwent imaging,which suggested a malignant periampullary tumor.Preoperative misdiagnosis of pancreatic cancer was made,and surgery was performed.Postoperative histopathology confirmed a duodenal GIST.The role of artificial intelligence in the diagnostic pathway is explored,emphasizing its potential to differentiate between duodenal GISTs and other similar conditions using advanced imaging analysis.CONCLUSION Artificial intelligence in radiomic imaging holds significant promise in enhancing the diagnostic process for rare cancers like duodenal GISTs,ensuring timely and accurate treatment.展开更多
Gastrointestinal(GI)cancers remain a leading cause of cancer-related morbidity and mortality worldwide.Artificial intelligence(AI),particularly machine learning and deep learning(DL),has shown promise in enhancing can...Gastrointestinal(GI)cancers remain a leading cause of cancer-related morbidity and mortality worldwide.Artificial intelligence(AI),particularly machine learning and deep learning(DL),has shown promise in enhancing cancer detection,diagnosis,and prognostication.A narrative review of literature published from January 2015 to march 2025 was conducted using PubMed,Web of Science,and Scopus.Search terms included"gastrointestinal cancer","artificial intelligence","machine learning","deep learning","radiomics","multimodal detection"and"predictive modeling".Studies were included if they focused on clinically relevant AI applications in GI oncology.AI algorithms for GI cancer detection have achieved high performance across imaging modalities,with endoscopic DL systems reporting accuracies of 85%-97%for polyp detection and segmentation.Radiomics-based models have predicted molecular biomarkers such as programmed cell death ligand 2 expression with area under the curves up to 0.92.Large language models applied to radiology reports demonstrated diagnostic accuracy comparable to junior radiologists(78.9%vs 80.0%),though without incremental value when combined with human interpretation.Multimodal AI approaches integrating imaging,pathology,and clinical data show emerging potential for precision oncology.AI in GI oncology has reached clinically relevant accuracy levels in multiple diagnostic tasks,with multimodal approaches and predictive biomarker modeling offering new opportunities for personalized care.However,broader validation,integration into clinical workflows,and attention to ethical,legal,and social implications remain critical for widespread adoption.展开更多
Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosupp...Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.展开更多
Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including ...Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including computed tomography(CT),magnetic resonance imaging(MRI),endoscopic imaging,and genomic profiles-to enable intelligent decision-making for individualized therapy.This approach leverages AI algorithms to fuse imaging,endoscopic,and omics data,facilitating comprehensive characterization of tumor biology,prediction of treatment response,and optimization of therapeutic strategies.By combining CT and MRI for structural assessment,endoscopic data for real-time visual inspection,and genomic information for molecular profiling,multimodal AI enhances the accuracy of patient stratification and treatment personalization.The clinical implementation of this technology demonstrates potential for improving patient outcomes,advancing precision oncology,and supporting individualized care in gastrointestinal cancers.Ultimately,multimodal AI serves as a transformative tool in oncology,bridging data integration with clinical application to effectively tailor therapies.展开更多
Metabolic dysfunction-associated steatotic liver disease(MASLD)is an increasingly prevalent condition associated with hepatic complications and cardiovascular and renal events.Given its significant clinical impact,the...Metabolic dysfunction-associated steatotic liver disease(MASLD)is an increasingly prevalent condition associated with hepatic complications and cardiovascular and renal events.Given its significant clinical impact,the development of new strategies for early diagnosis and treatment is essential to improve patient outcomes.Over the past decade,the integration of artificial intelligence(AI)into gastroenterology has led to transformative advancements in medical practice.AI represents a major step towards personalized medicine,offering the potential to enhance diagnostic accuracy,refine prognostic assessments,and optimize treatment strategies.Its applications are rapidly expanding.This article explores the emerging role of AI in the management of MASLD,emphasizing its ability to improve clinical prediction,enhance the diagnostic performance of imaging modalities,and support histopathological confirmation.Additionally,it examines the development of AI-guided personalized treatments,where lifestyle modifications and close monitoring play a pivotal role in achieving therapeutic success.展开更多
Healthy behavior has long been linked to mental health outcomes.However,the role of artificial intelligence(AI)literacy in shaping healthy behaviors and its potential impact on mental health remains underexplored.This...Healthy behavior has long been linked to mental health outcomes.However,the role of artificial intelligence(AI)literacy in shaping healthy behaviors and its potential impact on mental health remains underexplored.This paper presents a scoping review offering a novel perspective on the intersection of healthy behaviors,mental health,and AI literacy.By examining how individuals’understanding of AI influences their choices regarding nutrition and their susceptibility to mental health issues,the current study explores emerging trends in health behavior decision-making.This emphasizes the need for integrating AI literacy into mental health and health behaviors education,as well as the development of AI-driven tools to support healthier behavior choices.It highlights that individuals with low AI literacy may misinterpret or overly depend on AI guidance,resulting in maladaptive health choices,while those with high AI literacy may be more likely to engage reflectively and sustain positive behaviors.The paper outlines the importance of inclusive education,user-centered design,and community-based support systems to enhance AI literacy for digitally marginalized groups.AI literacy may be positioned as a key determinant of health equity,better allowing for interdisciplinary strategies that empower individuals to make informed,autonomous decisions that promote both physical and mental health.展开更多
The thermal conductivity of nanofluids is an important property that influences the heat transfer capabilities of nanofluids.Researchers rely on experimental investigations to explore nanofluid properties,as it is a n...The thermal conductivity of nanofluids is an important property that influences the heat transfer capabilities of nanofluids.Researchers rely on experimental investigations to explore nanofluid properties,as it is a necessary step before their practical application.As these investigations are time and resource-consuming undertakings,an effective prediction model can significantly improve the efficiency of research operations.In this work,an Artificial Neural Network(ANN)model is developed to predict the thermal conductivity of metal oxide water-based nanofluid.For this,a comprehensive set of 691 data points was collected from the literature.This dataset is split into training(70%),validation(15%),and testing(15%)and used to train the ANN model.The developed model is a backpropagation artificial neural network with a 4–12–1 architecture.The performance of the developed model shows high accuracy with R values above 0.90 and rapid convergence.It shows that the developed ANN model accurately predicts the thermal conductivity of nanofluids.展开更多
Functional gastrointestinal disorders(FGIDs),including irritable bowel syndrome(IBS),functional dyspepsia(FD),and gastroesophageal reflux disease(GERD),present persistent diagnostic and therapeutic challenges due to s...Functional gastrointestinal disorders(FGIDs),including irritable bowel syndrome(IBS),functional dyspepsia(FD),and gastroesophageal reflux disease(GERD),present persistent diagnostic and therapeutic challenges due to symptom heterogeneity and the absence of reliable biomarkers.Artificial intelligence(AI)enables the integration of multimodal data to enhance FGID management through precision diagnostics and preventive healthcare.This minireview summarizes recent advancements in AI applications for FGIDs,highlighting progress in diagnostic accuracy,subtype classification,personalized interventions,and preventive strategies inspired by the traditional Chinese medicine concept of“treating the undiseased”.Machine learning and deep learning algorithms have demonstrated value in improving IBS diagnosis,refining FD neuro-gastrointestinal subtyping,and screening for GERD-related complications.Moreover,AI supports dietary,psychological,and integrative medicine-based interventions to improve patient adherence and quality of life.Nonetheless,key challenges remain,including data heterogeneity,limited model interpretability,and the need for robust clinical validation.Future directions emphasize interdisciplinary collaboration,the development of multimodal and explainable AI models,and the creation of patientcentered platforms to facilitate a shift from reactive treatment to proactive prevention.This review provides a systematic framework to guide the clinical application and theoretical innovation of AI in FGIDs.展开更多
Background:Medical artificial intelligence(MAI)is a synthesis of medical science and artificial intelligence development,serving as a crucial field in the current advancement and application of AI.In the process of de...Background:Medical artificial intelligence(MAI)is a synthesis of medical science and artificial intelligence development,serving as a crucial field in the current advancement and application of AI.In the process of developing medical AI,there may arise not only legal risks such as infringement of privacy rights and health rights but also ethical risks stemming from violations of the principles of beneficence and non-maleficence.Methods:To effectively address the damages caused by MAI in the future,it is necessary to establish a hierarchical governance system with MAI.This paper examines the systematic collection of local practices in China and the induction and integration of legal remedies for the damage of MAI.Results:To effectively address the ethical and legal challenges of medical artificial intelligence,a hierarchical regulatory system should be established,which based on the impact of intervention measures on natural rights and differences in intervention timing.This paper finally obtains a legal hierarchical governance system corresponding to the ethical risks and legal risks of MAI in China.Conclusion:The Chinese government has formed a multi-agent governance system based on the impact of risks on rights and the timing of legal intervention,which provides a reference for other countries to follow up on the research on MAI risk management.展开更多
To enhance the electrochemical performance of lithium-ion battery anodes with higher silicon content,it is essential to engineer their microstructure for better lithium-ion transport and mitigated volume change as wel...To enhance the electrochemical performance of lithium-ion battery anodes with higher silicon content,it is essential to engineer their microstructure for better lithium-ion transport and mitigated volume change as well.Herein,we suggest an effective approach to control the micropore structure of silicon oxide(SiO_(x))/artificial graphite(AG)composite electrodes using a perforated current collector.The electrode features a unique pore structure,where alternating high-porosity domains and low-porosity domains markedly reduce overall electrode resistance,leading to a 20%improvement in rate capability at a 5C-rate discharge condition.Using microstructure-resolved modeling and simulations,we demonstrate that the patterned micropore structure enhances lithium-ion transport,mitigating the electrolyte concentration gradient of lithium-ion.Additionally,perforating current collector with a chemical etching process increases the number of hydrogen bonding sites and enlarges the interface with the SiO_(x)/AG composite electrode,significantly improving adhesion strength.This,in turn,suppresses mechanical degradation and leads to a 50%higher capacity retention.Thus,regularly arranged micropore structure enabled by the perforated current collector successfully improves both rate capability and cycle life in SiO_(x)/AG composite electrodes,providing valuable insights into electrode engineering.展开更多
The effects of artificial aging(T6)on the creep resistance with tensile stresses in the range of 50−80 MPa at 175℃were investigated for an extruded Mg−1.22Al−0.31Ca−0.44Mn(wt.%)alloy.The Guinier-Preston(G.P.)zones pr...The effects of artificial aging(T6)on the creep resistance with tensile stresses in the range of 50−80 MPa at 175℃were investigated for an extruded Mg−1.22Al−0.31Ca−0.44Mn(wt.%)alloy.The Guinier-Preston(G.P.)zones primarily precipitate in the sample aged at 200℃for 1 h(T6-200℃/1h),while the Al_(2)Ca phases mainly precipitate in the sample aged at 275℃for 8 h(T6-275℃/8h).The T6-200℃/1h sample exhibits excellent creep resistance,with a steady-state creep rate one order of magnitude lower than that of the T6-275℃/8h sample.The abnormally high stress exponent(~8.2)observed in the T6-200℃/1h sample is associated with the power-law breakdown mechanism.TEM analysis illuminates that the creep mechanism for the T6-200℃/1h sample is cross-slip between basal and prismatic dislocations,while the T6-275℃/8h sample exhibits a mixed mechanism of dislocation cross-slip and climb.Compared with the Al_(2)Ca phase,the dense G.P.zones effectively impede dislocation climb and glide during the creep process,demonstrating superior creep resistance of the T6-200℃/1h sample.展开更多
To investigate the evacuation behaviors of pedestrians considering the action of guards and to develop an effective evacuation strategy in an artificial attack, an extended floor field model is proposed. In this model...To investigate the evacuation behaviors of pedestrians considering the action of guards and to develop an effective evacuation strategy in an artificial attack, an extended floor field model is proposed. In this model, the artificial attacker's assault on pedestrians, the death of pedestrians, and the guard's capture are involved simultaneously. An alternative evacuation strategy which can largely reduce the number of casualties is developed and the effects of several key parameters such as the deterrence radius and capture distance on evacuation dynamics are studied. The results show that congestion near the exit has dual effects. More specifically, the guard can catch all attackers in a short time because the artificial attackers have a more concentrated distribution, but more casualties can occur because it is hard for pedestrians to escape the assault due to congestion. In contrast, when pedestrians have more preference of approaching the guard, although the guard will take more time to capture the attackers resulting from the dispersion of the attackers, the death toll will decrease. One of the reasons is the dispersal of the crowd, and the decrease in congestion is beneficial for escape. The other is that the attackers will be caught before launching the attack on the people who are around the guard, in other words, the guard protects a large number of pedestrians from being killed. Moreover, increasing capture distance of the guard can effectively reduce the casualties and the catch time. As the deterrence radius reflecting the tendency of escaping from the guard for attackers rises, it becomes more difficult for the guard to catch the attackers and more casualties are caused. However, when the deterrence radius reaches a certain level, the number of deaths is reduced because the attackers prefer to stay as far away as possible from the guard rather than occupy a position where they could assault more people.展开更多
The bearing capacity of interfering footings located near the slope face suffers from reduced bearing capacity due to the formation of the curtailed passive zone. Depending upon the position of the footing, their spac...The bearing capacity of interfering footings located near the slope face suffers from reduced bearing capacity due to the formation of the curtailed passive zone. Depending upon the position of the footing, their spacing and steepness of the slope different extents of bearing capacity reduction can be exhibited. A series of finite element investigation has been done with the aid of Plaxis 3 D v AE.01 to elucidate the influence of various geotechnical and geometrical parameters on the ultimate bearing capacity of interfering surface strip footings located at the crest of the natural soil slope. Based on the large database obtained from the numerical simulation, a6-8-1 Artificial Neural Network architecture has been considered for the assessment of the ultimate bearing capacity of interfering strip footings placed on the crest of natural soil slope. Sensitivity analyses have been conducted to establish the relative significance of the contributory parameters, which exhibited that for the stated problem, apart from shear strength parameters, the setback ratio and spacing of footing are the prime contributory parameters.展开更多
As human activities increase,artificially modified terrain is increasingly widely distributed in road,hydrological,and urban construction.Artificially modified terrain plays an important role in protecting from geolog...As human activities increase,artificially modified terrain is increasingly widely distributed in road,hydrological,and urban construction.Artificially modified terrain plays an important role in protecting from geological disasters and in the planning and design of urban landscapes.Compared with natural slopes,artificial slopes have obvious morphological characteristics.Traditional modeling methods are no longer suitable for digital elevation model(DEM)modeling of artificial slopes because they often seriously distort the DEM results.In this paper,from the perspective of morphological characteristics,artificial slopes are divided into two types,namely,regular slopes and irregular slopes,based on whether the top and bottom lines of the artificial slope are parallel.Then,according to the morphological characteristics of the two types of slopes,the following DEM construction methods are designed:the first method(perpendicular+inverse distance weighted)is suitable for regular slopes,and the second method(perpendicular+high-accuracy surface modeling)is suitable for irregular slopes.Finally,a DEM construction test is carried out using the artificial slopes in the study area.The results show that for the regular and irregular slopes in the study area,the construction method proposed in this paper has significant advantages in morphological accuracy over the traditional method(triangulated irregular network),and the elevation accuracy method is also superior to the traditional method(using this method,the mean error and standard deviation error of the regular slope DEM are 0.08 m and 0.13 m,respectively,and those of the irregular slope DEM are 0.08 m and 0.06 m).In addition,the top lines and bottom lines can be included in the DEM construction of the background area after processing the elevation information of the boundary line to realize a smooth transition in the boundary between the artificial slope and the background area.展开更多
文摘With gastric cancer ranking among the most prevalent and deadly malignancies worldwide,early detection and individualized prognosis remain essential for improving patient outcomes.This letter discusses recent advancements in arti-ficial intelligence(AI)-driven predictive tools for gastric cancer,emphasizing a computed tomography-based radiomic model that achieved a predictive accuracy of area under the curve of 0.893 for treatment response in advanced cases undergoing neoadjuvant immunochemotherapy.AI offers promising avenues for predictive accuracy and personalized treatment planning in gastric oncology.Additionally,this letter highlights the comparison of these AI tools with tra-ditional methodologies,demonstrating their potential to streamline clinical workflows and address existing gaps in risk stratification and early detection.Furthermore,this letter addresses the ethical considerations and the need for robust clinical-AI collaboration to achieve reliable,transparent,and unbiased outcomes.Strengthening cross-disciplinary efforts will be vital for the responsible and effective deployment of AI in this critical area of oncology.
基金Ministry of Justice of China Funding 22SFB5044:Research on the optimization and governance strategies of intellectual property ecosystem empowered by blockchain technology。
文摘Embodied intelligence represents a new paradigm for the cross-integration development of artificial intelli⁃gence.By endowing AI with a"physical body",it enables interaction with the real world,allowing AI to move beyond digital environments into the physical realm and demonstrate intelligence that simulates or even surpasses human capa⁃bilities.Although embodied artificial intelligence demonstrates substantial potential in the realm of invention and cre⁃ation,there remain challenges in obtaining patent authorization for its generated technical solutions,specifically con⁃cerning subject,object,and market aspects.To address these issues,the feasibility of the subject should be demon⁃strated from the perspective of embodied cognition theory,while the object should be justified from a techno-centric standpoint.Subsequently,a regulatory framework for the patentability of technical solutions generated by embodied in⁃telligence should be proposed.First,a more inclusive subject framework should be established,recognizing embodied artificial intelligence as an inventor alongside humans,thereby affirming a coexistent"inventor"identity.Second,pat⁃ent rights should be assigned to developers of embodied artificial intelligence,referencing the rights distribution para⁃digm under employment relationships.Third,the criteria for patent eligibility and the"three-aspect"examination stan⁃dards should be refined.Finally,mechanisms for optimizing the implementation of rights and risk prevention should be developed.
文摘Psychosomatic disorders,characterized by significant contributions of psychosocial factors to the pathogenesis and progression of somatic organic diseases or functional impairments(e.g.,diabetes,essential hypertension,asthma,inflammatory bowel disease,and neurodermatitis),present unique diagnostic and therapeutic challenges[1].Traditional diagnostic frameworks,heavily reliant on clinicians’subjective judgment and limited by the qualitative nature of psychological assessments,often result in misdiagnosis or delayed detection.As a cornerstone of the Fourth Industrial Revolution,artificial intelligence(AI)has demonstrated transformative potential in medicine.In psychosomatic medicine,AI leverages advanced data analytics,machine learning,and natural language processing to decipher the intricate interplay between psychological and physiological mechanisms,offering novel tools for diagnosis,treatment,and prevention.However,its clinical integration raises critical ethical and operational concerns that warrant rigorous examination.
文摘Efficient working capital management(WCM)creates value for both management and shareholders by enhancing cash flows and reducing investment in receivables and inventory.It supports liquidity and minimizes financial distress risks,aligning with the goal of shareholder value maximization.However,traditional manual approaches to WCM are no longer sufficient due to the rapid and complex changes in economic and business environments.As a result,firms increasingly rely on artificial intelligence(AI)in WCM.AI offers advanced capabilities in prediction,monitoring,and problem-solving by processing vast data,identifying variable relationships,and adapting to change faster than human cognition.This paper explores the fundamentals of WCM and AI,their interconnections,and the strategic opportunities AI introduces to optimize WCM in modern enterprises.
基金Supported by Japan Society for the Promotion of Science,No.24K11935.
文摘This review comprehensively summarized the potential of artificial intelligence(AI)in the management of esophageal cancer.It highlighted the significance of AI-assisted endoscopy in Japan where endoscopy is central to both screening and diagnosis.For the clinical adaptation of AI,several challenges remain for its effective translation.The establishment of high-quality clinical databases,such as the National Clinical Database and Japan Endoscopy Database in Japan,which covers almost all cases of esophageal cancer,is essential for validating multimodal AI models.This requires rigorous external validation using diverse datasets,including those from different endoscope manufacturers and image qualities.Furthermore,endoscopists’skills significantly affect diagnostic accuracy,suggesting that AI should serve as a supportive tool rather than a replacement.Addressing these challenges,along with country-specific legal and ethical considerations,will facilitate the successful integration of multimodal AI into the management of esophageal cancer,particularly in endoscopic diagnosis,and contribute to improved patient outcomes.Although this review focused on Japan as a case study,the challenges and solutions described are broadly applicable to other high-incidence regions.
文摘Artificial intelligence(AI)is revolutionizing medical imaging,particularly in chronic liver diseases assessment.AI technologies,including machine learning and deep learning,are increasingly integrated with multiparametric ultrasound(US)techniques to provide more accurate,objective,and non-invasive evaluations of liver fibrosis and steatosis.Analyzing large datasets from US images,AI enhances diagnostic precision,enabling better quantification of liver stiffness and fat content,which are essential for diagnosing and staging liver fibrosis and steatosis.Combining advanced US modalities,such as elastography and doppler imaging with AI,has demonstrated improved sensitivity in identifying different stages of liver disease and distinguishing various degrees of steatotic liver.These advancements also contribute to greater reproducibility and reduced operator dependency,addressing some of the limitations of traditional methods.The clinical implications of AI in liver disease are vast,ranging from early detection to predicting disease progression and evaluating treatment response.Despite these promising developments,challenges such as the need for large-scale datasets,algorithm transparency,and clinical validation remain.The aim of this review is to explore the current applications and future potential of AI in liver fibrosis and steatosis assessment using multiparametric US,highlighting the technological advances and clinical relevance of this emerging field.
文摘BACKGROUND Gastrointestinal stromal tumors(GISTs)are rare mesenchymal neoplasms primarily originating in the stomach or small intestine.Duodenal GISTs are particularly uncommon,accounting for only a small fraction of GIST cases.These tumors often present with nonspecific symptoms,making early detection challenging.This case discusses a duodenal GIST misdiagnosed as pancreatic cancer due to obstructive jaundice.CASE SUMMARY A 40-year-old male with jaundice and abdominal symptoms underwent imaging,which suggested a malignant periampullary tumor.Preoperative misdiagnosis of pancreatic cancer was made,and surgery was performed.Postoperative histopathology confirmed a duodenal GIST.The role of artificial intelligence in the diagnostic pathway is explored,emphasizing its potential to differentiate between duodenal GISTs and other similar conditions using advanced imaging analysis.CONCLUSION Artificial intelligence in radiomic imaging holds significant promise in enhancing the diagnostic process for rare cancers like duodenal GISTs,ensuring timely and accurate treatment.
文摘Gastrointestinal(GI)cancers remain a leading cause of cancer-related morbidity and mortality worldwide.Artificial intelligence(AI),particularly machine learning and deep learning(DL),has shown promise in enhancing cancer detection,diagnosis,and prognostication.A narrative review of literature published from January 2015 to march 2025 was conducted using PubMed,Web of Science,and Scopus.Search terms included"gastrointestinal cancer","artificial intelligence","machine learning","deep learning","radiomics","multimodal detection"and"predictive modeling".Studies were included if they focused on clinically relevant AI applications in GI oncology.AI algorithms for GI cancer detection have achieved high performance across imaging modalities,with endoscopic DL systems reporting accuracies of 85%-97%for polyp detection and segmentation.Radiomics-based models have predicted molecular biomarkers such as programmed cell death ligand 2 expression with area under the curves up to 0.92.Large language models applied to radiology reports demonstrated diagnostic accuracy comparable to junior radiologists(78.9%vs 80.0%),though without incremental value when combined with human interpretation.Multimodal AI approaches integrating imaging,pathology,and clinical data show emerging potential for precision oncology.AI in GI oncology has reached clinically relevant accuracy levels in multiple diagnostic tasks,with multimodal approaches and predictive biomarker modeling offering new opportunities for personalized care.However,broader validation,integration into clinical workflows,and attention to ethical,legal,and social implications remain critical for widespread adoption.
文摘Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.
基金Supported by Xuhui District Health Commission,No.SHXH202214.
文摘Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including computed tomography(CT),magnetic resonance imaging(MRI),endoscopic imaging,and genomic profiles-to enable intelligent decision-making for individualized therapy.This approach leverages AI algorithms to fuse imaging,endoscopic,and omics data,facilitating comprehensive characterization of tumor biology,prediction of treatment response,and optimization of therapeutic strategies.By combining CT and MRI for structural assessment,endoscopic data for real-time visual inspection,and genomic information for molecular profiling,multimodal AI enhances the accuracy of patient stratification and treatment personalization.The clinical implementation of this technology demonstrates potential for improving patient outcomes,advancing precision oncology,and supporting individualized care in gastrointestinal cancers.Ultimately,multimodal AI serves as a transformative tool in oncology,bridging data integration with clinical application to effectively tailor therapies.
文摘Metabolic dysfunction-associated steatotic liver disease(MASLD)is an increasingly prevalent condition associated with hepatic complications and cardiovascular and renal events.Given its significant clinical impact,the development of new strategies for early diagnosis and treatment is essential to improve patient outcomes.Over the past decade,the integration of artificial intelligence(AI)into gastroenterology has led to transformative advancements in medical practice.AI represents a major step towards personalized medicine,offering the potential to enhance diagnostic accuracy,refine prognostic assessments,and optimize treatment strategies.Its applications are rapidly expanding.This article explores the emerging role of AI in the management of MASLD,emphasizing its ability to improve clinical prediction,enhance the diagnostic performance of imaging modalities,and support histopathological confirmation.Additionally,it examines the development of AI-guided personalized treatments,where lifestyle modifications and close monitoring play a pivotal role in achieving therapeutic success.
文摘Healthy behavior has long been linked to mental health outcomes.However,the role of artificial intelligence(AI)literacy in shaping healthy behaviors and its potential impact on mental health remains underexplored.This paper presents a scoping review offering a novel perspective on the intersection of healthy behaviors,mental health,and AI literacy.By examining how individuals’understanding of AI influences their choices regarding nutrition and their susceptibility to mental health issues,the current study explores emerging trends in health behavior decision-making.This emphasizes the need for integrating AI literacy into mental health and health behaviors education,as well as the development of AI-driven tools to support healthier behavior choices.It highlights that individuals with low AI literacy may misinterpret or overly depend on AI guidance,resulting in maladaptive health choices,while those with high AI literacy may be more likely to engage reflectively and sustain positive behaviors.The paper outlines the importance of inclusive education,user-centered design,and community-based support systems to enhance AI literacy for digitally marginalized groups.AI literacy may be positioned as a key determinant of health equity,better allowing for interdisciplinary strategies that empower individuals to make informed,autonomous decisions that promote both physical and mental health.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2021R1A6A1A10044950).
文摘The thermal conductivity of nanofluids is an important property that influences the heat transfer capabilities of nanofluids.Researchers rely on experimental investigations to explore nanofluid properties,as it is a necessary step before their practical application.As these investigations are time and resource-consuming undertakings,an effective prediction model can significantly improve the efficiency of research operations.In this work,an Artificial Neural Network(ANN)model is developed to predict the thermal conductivity of metal oxide water-based nanofluid.For this,a comprehensive set of 691 data points was collected from the literature.This dataset is split into training(70%),validation(15%),and testing(15%)and used to train the ANN model.The developed model is a backpropagation artificial neural network with a 4–12–1 architecture.The performance of the developed model shows high accuracy with R values above 0.90 and rapid convergence.It shows that the developed ANN model accurately predicts the thermal conductivity of nanofluids.
基金Supported by The Natural Science Foundation of China,No.82374292the Plans for Major Provincial Science and Technology Projects of Anhui Province,No.202303a07020003the Innovation Team and Talents Cultivation Program of the National Administration of Traditional Chinese Medicine,No.ZYYCXTD-C-202401.
文摘Functional gastrointestinal disorders(FGIDs),including irritable bowel syndrome(IBS),functional dyspepsia(FD),and gastroesophageal reflux disease(GERD),present persistent diagnostic and therapeutic challenges due to symptom heterogeneity and the absence of reliable biomarkers.Artificial intelligence(AI)enables the integration of multimodal data to enhance FGID management through precision diagnostics and preventive healthcare.This minireview summarizes recent advancements in AI applications for FGIDs,highlighting progress in diagnostic accuracy,subtype classification,personalized interventions,and preventive strategies inspired by the traditional Chinese medicine concept of“treating the undiseased”.Machine learning and deep learning algorithms have demonstrated value in improving IBS diagnosis,refining FD neuro-gastrointestinal subtyping,and screening for GERD-related complications.Moreover,AI supports dietary,psychological,and integrative medicine-based interventions to improve patient adherence and quality of life.Nonetheless,key challenges remain,including data heterogeneity,limited model interpretability,and the need for robust clinical validation.Future directions emphasize interdisciplinary collaboration,the development of multimodal and explainable AI models,and the creation of patientcentered platforms to facilitate a shift from reactive treatment to proactive prevention.This review provides a systematic framework to guide the clinical application and theoretical innovation of AI in FGIDs.
基金funded by China Law Society 2025 Annual Legal Research,Project grant number:CLS(2025)Y04.
文摘Background:Medical artificial intelligence(MAI)is a synthesis of medical science and artificial intelligence development,serving as a crucial field in the current advancement and application of AI.In the process of developing medical AI,there may arise not only legal risks such as infringement of privacy rights and health rights but also ethical risks stemming from violations of the principles of beneficence and non-maleficence.Methods:To effectively address the damages caused by MAI in the future,it is necessary to establish a hierarchical governance system with MAI.This paper examines the systematic collection of local practices in China and the induction and integration of legal remedies for the damage of MAI.Results:To effectively address the ethical and legal challenges of medical artificial intelligence,a hierarchical regulatory system should be established,which based on the impact of intervention measures on natural rights and differences in intervention timing.This paper finally obtains a legal hierarchical governance system corresponding to the ethical risks and legal risks of MAI in China.Conclusion:The Chinese government has formed a multi-agent governance system based on the impact of risks on rights and the timing of legal intervention,which provides a reference for other countries to follow up on the research on MAI risk management.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.NRF-2021M3H4A1A02048529)the Ministry of Trade,Industry and Energy(MOTIE)of the Korean government under grant No.RS-2022-00155854support from the DGIST Supercomputing and Big Data Center.
文摘To enhance the electrochemical performance of lithium-ion battery anodes with higher silicon content,it is essential to engineer their microstructure for better lithium-ion transport and mitigated volume change as well.Herein,we suggest an effective approach to control the micropore structure of silicon oxide(SiO_(x))/artificial graphite(AG)composite electrodes using a perforated current collector.The electrode features a unique pore structure,where alternating high-porosity domains and low-porosity domains markedly reduce overall electrode resistance,leading to a 20%improvement in rate capability at a 5C-rate discharge condition.Using microstructure-resolved modeling and simulations,we demonstrate that the patterned micropore structure enhances lithium-ion transport,mitigating the electrolyte concentration gradient of lithium-ion.Additionally,perforating current collector with a chemical etching process increases the number of hydrogen bonding sites and enlarges the interface with the SiO_(x)/AG composite electrode,significantly improving adhesion strength.This,in turn,suppresses mechanical degradation and leads to a 50%higher capacity retention.Thus,regularly arranged micropore structure enabled by the perforated current collector successfully improves both rate capability and cycle life in SiO_(x)/AG composite electrodes,providing valuable insights into electrode engineering.
基金supported by the National Natural Science Foundation of China (Nos. 52175322, 52271031)the Natural Science Foundation of Jilin Province, China (No. SKL202302015)。
文摘The effects of artificial aging(T6)on the creep resistance with tensile stresses in the range of 50−80 MPa at 175℃were investigated for an extruded Mg−1.22Al−0.31Ca−0.44Mn(wt.%)alloy.The Guinier-Preston(G.P.)zones primarily precipitate in the sample aged at 200℃for 1 h(T6-200℃/1h),while the Al_(2)Ca phases mainly precipitate in the sample aged at 275℃for 8 h(T6-275℃/8h).The T6-200℃/1h sample exhibits excellent creep resistance,with a steady-state creep rate one order of magnitude lower than that of the T6-275℃/8h sample.The abnormally high stress exponent(~8.2)observed in the T6-200℃/1h sample is associated with the power-law breakdown mechanism.TEM analysis illuminates that the creep mechanism for the T6-200℃/1h sample is cross-slip between basal and prismatic dislocations,while the T6-275℃/8h sample exhibits a mixed mechanism of dislocation cross-slip and climb.Compared with the Al_(2)Ca phase,the dense G.P.zones effectively impede dislocation climb and glide during the creep process,demonstrating superior creep resistance of the T6-200℃/1h sample.
基金Project supported by the National Key Research and Development Program of China(Grant No.2017YFC0804900)the National Natural Science Foundation of China(Grant Nos.71790613 and 51534008)
文摘To investigate the evacuation behaviors of pedestrians considering the action of guards and to develop an effective evacuation strategy in an artificial attack, an extended floor field model is proposed. In this model, the artificial attacker's assault on pedestrians, the death of pedestrians, and the guard's capture are involved simultaneously. An alternative evacuation strategy which can largely reduce the number of casualties is developed and the effects of several key parameters such as the deterrence radius and capture distance on evacuation dynamics are studied. The results show that congestion near the exit has dual effects. More specifically, the guard can catch all attackers in a short time because the artificial attackers have a more concentrated distribution, but more casualties can occur because it is hard for pedestrians to escape the assault due to congestion. In contrast, when pedestrians have more preference of approaching the guard, although the guard will take more time to capture the attackers resulting from the dispersion of the attackers, the death toll will decrease. One of the reasons is the dispersal of the crowd, and the decrease in congestion is beneficial for escape. The other is that the attackers will be caught before launching the attack on the people who are around the guard, in other words, the guard protects a large number of pedestrians from being killed. Moreover, increasing capture distance of the guard can effectively reduce the casualties and the catch time. As the deterrence radius reflecting the tendency of escaping from the guard for attackers rises, it becomes more difficult for the guard to catch the attackers and more casualties are caused. However, when the deterrence radius reaches a certain level, the number of deaths is reduced because the attackers prefer to stay as far away as possible from the guard rather than occupy a position where they could assault more people.
文摘The bearing capacity of interfering footings located near the slope face suffers from reduced bearing capacity due to the formation of the curtailed passive zone. Depending upon the position of the footing, their spacing and steepness of the slope different extents of bearing capacity reduction can be exhibited. A series of finite element investigation has been done with the aid of Plaxis 3 D v AE.01 to elucidate the influence of various geotechnical and geometrical parameters on the ultimate bearing capacity of interfering surface strip footings located at the crest of the natural soil slope. Based on the large database obtained from the numerical simulation, a6-8-1 Artificial Neural Network architecture has been considered for the assessment of the ultimate bearing capacity of interfering strip footings placed on the crest of natural soil slope. Sensitivity analyses have been conducted to establish the relative significance of the contributory parameters, which exhibited that for the stated problem, apart from shear strength parameters, the setback ratio and spacing of footing are the prime contributory parameters.
基金supported by Key Project of Natural Science Research of Anhui Provincial Department of Education(No.KJ2020A0722,No.KJ2020A0721,No.KJ2020A0705)Major Project of Natural Science Research of Anhui Provincial Department of Education(No.KJ2021ZD0130)+3 种基金General Project of Natural Science Research of Anhui Provincial Department of Education(No.KJ2020B01,No.KJ2020B02)The guiding plan project of Chuzhou science and Technology Bureau(No.2021ZD008)Grant from State Key Laboratory of Resources and Environmental Information System in 2018the Key Project of Research and Development in Chuzhou Science and Technology Program(No.2020ZG016)。
文摘As human activities increase,artificially modified terrain is increasingly widely distributed in road,hydrological,and urban construction.Artificially modified terrain plays an important role in protecting from geological disasters and in the planning and design of urban landscapes.Compared with natural slopes,artificial slopes have obvious morphological characteristics.Traditional modeling methods are no longer suitable for digital elevation model(DEM)modeling of artificial slopes because they often seriously distort the DEM results.In this paper,from the perspective of morphological characteristics,artificial slopes are divided into two types,namely,regular slopes and irregular slopes,based on whether the top and bottom lines of the artificial slope are parallel.Then,according to the morphological characteristics of the two types of slopes,the following DEM construction methods are designed:the first method(perpendicular+inverse distance weighted)is suitable for regular slopes,and the second method(perpendicular+high-accuracy surface modeling)is suitable for irregular slopes.Finally,a DEM construction test is carried out using the artificial slopes in the study area.The results show that for the regular and irregular slopes in the study area,the construction method proposed in this paper has significant advantages in morphological accuracy over the traditional method(triangulated irregular network),and the elevation accuracy method is also superior to the traditional method(using this method,the mean error and standard deviation error of the regular slope DEM are 0.08 m and 0.13 m,respectively,and those of the irregular slope DEM are 0.08 m and 0.06 m).In addition,the top lines and bottom lines can be included in the DEM construction of the background area after processing the elevation information of the boundary line to realize a smooth transition in the boundary between the artificial slope and the background area.
