Objective This study aimed to evaluate and compare the effectiveness of knowledge base-optimized and unoptimized large language models(LLMs)in the field of orthopedics to explore optimization strategies for the applic...Objective This study aimed to evaluate and compare the effectiveness of knowledge base-optimized and unoptimized large language models(LLMs)in the field of orthopedics to explore optimization strategies for the application of LLMs in specific fields.Methods This research constructed a specialized knowledge base using clinical guidelines from the American Academy of Orthopaedic Surgeons(AAOS)and authoritative orthopedic publications.A total of 30 orthopedic-related questions covering aspects such as anatomical knowledge,disease diagnosis,fracture classification,treatment options,and surgical techniques were input into both the knowledge base-optimized and unoptimized versions of the GPT-4,ChatGLM,and Spark LLM,with their generated responses recorded.The overall quality,accuracy,and comprehensiveness of these responses were evaluated by 3 experienced orthopedic surgeons.Results Compared with their unoptimized LLMs,the optimized version of GPT-4 showed improvements of 15.3%in overall quality,12.5%in accuracy,and 12.8%in comprehensiveness;ChatGLM showed improvements of 24.8%,16.1%,and 19.6%,respectively;and Spark LLM showed improvements of 6.5%,14.5%,and 24.7%,respectively.Conclusion The optimization of knowledge bases significantly enhances the quality,accuracy,and comprehensiveness of the responses provided by the 3 models in the orthopedic field.Therefore,knowledge base optimization is an effective method for improving the performance of LLMs in specific fields.展开更多
The occurrence of major emergencies often leads to environmental damage,property damage,health challenges and life threats.Despite the tremendous progress we have made in responding to the many challenges posed by dis...The occurrence of major emergencies often leads to environmental damage,property damage,health challenges and life threats.Despite the tremendous progress we have made in responding to the many challenges posed by disasters in recent years,there are still many shortcomings.As an emerging technology widely used in recent years,virtual reality(VR)technology is very suitable for many fields of disaster medicine,such as basic education,professional training,psychotherapy,etc.The purpose of this review article is to introduce the application of VR technology in the disaster medical field and prospect its trend in the future.展开更多
As modern science and technology constantly progresses,the fields of artificial intelligence,mixed reality technology,remote technology,etc.have rapidly developed.Meanwhile,these technologies have been gradually appli...As modern science and technology constantly progresses,the fields of artificial intelligence,mixed reality technology,remote technology,etc.have rapidly developed.Meanwhile,these technologies have been gradually applied to the medical field,leading to the development of intelligent medicine.What’s more,intelligent medicine has greatly promoted the development of traditional Chinese medicine(TCM),causing huge changes in the diagnosis of TCM ailments,remote treatment,teaching,etc.Therefore,there are both opportunities and challenges for inheriting and developing TCM.Herein,the related research progress of intelligent medicine in the TCM in China and abroad over the years is analyzed,with the purpose of introducing the present application status of intelligent medicine in TCM and providing reference for the inheritance and development of TCM in a new era.展开更多
Objective:To explore a new artificial intelligence(AI)-aided method to assist the clinical diagnosis of tibial plateau fractures(TPFs)and further measure its validity and feasibility.Methods:A total of 542 X-rays of T...Objective:To explore a new artificial intelligence(AI)-aided method to assist the clinical diagnosis of tibial plateau fractures(TPFs)and further measure its validity and feasibility.Methods:A total of 542 X-rays of TPFs were collected as a reference database.An AI algorithm(RetinaNet)was trained to analyze and detect TPF on the X-rays.The ability of the AI algorithm was determined by indexes such as detection accuracy and time taken for analysis.The algorithm performance was also compared with orthopedic physicians.Results:The AI algorithm showed a detection accuracy of 0.91 for the identification of TPF,which was similar to the performance of orthopedic physicians(0.92±0.03).The average time spent for analysis of the AI was 0.56 s,which was 16 times faster than human performance(8.44±3.26 s).Conclusion:The AI algorithm is a valid and efficient method for the clinical diagnosis of TPF.It can be a useful assistant for orthopedic physicians,which largely promotes clinical workflow and further guarantees the health and security of patients.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.81974355 and No.82172524).
文摘Objective This study aimed to evaluate and compare the effectiveness of knowledge base-optimized and unoptimized large language models(LLMs)in the field of orthopedics to explore optimization strategies for the application of LLMs in specific fields.Methods This research constructed a specialized knowledge base using clinical guidelines from the American Academy of Orthopaedic Surgeons(AAOS)and authoritative orthopedic publications.A total of 30 orthopedic-related questions covering aspects such as anatomical knowledge,disease diagnosis,fracture classification,treatment options,and surgical techniques were input into both the knowledge base-optimized and unoptimized versions of the GPT-4,ChatGLM,and Spark LLM,with their generated responses recorded.The overall quality,accuracy,and comprehensiveness of these responses were evaluated by 3 experienced orthopedic surgeons.Results Compared with their unoptimized LLMs,the optimized version of GPT-4 showed improvements of 15.3%in overall quality,12.5%in accuracy,and 12.8%in comprehensiveness;ChatGLM showed improvements of 24.8%,16.1%,and 19.6%,respectively;and Spark LLM showed improvements of 6.5%,14.5%,and 24.7%,respectively.Conclusion The optimization of knowledge bases significantly enhances the quality,accuracy,and comprehensiveness of the responses provided by the 3 models in the orthopedic field.Therefore,knowledge base optimization is an effective method for improving the performance of LLMs in specific fields.
基金This study was supported by grants from the National Natural Science Foundation of China(No.81974355)Major Project of Technological Innovation of Hubei(No.2018AAA067)Excellent Projects Funded by Science and Technological of Returned Students from Ministry of Personnel and Social Affairs(No.2016-176).
文摘The occurrence of major emergencies often leads to environmental damage,property damage,health challenges and life threats.Despite the tremendous progress we have made in responding to the many challenges posed by disasters in recent years,there are still many shortcomings.As an emerging technology widely used in recent years,virtual reality(VR)technology is very suitable for many fields of disaster medicine,such as basic education,professional training,psychotherapy,etc.The purpose of this review article is to introduce the application of VR technology in the disaster medical field and prospect its trend in the future.
基金supported by grants from the National Natural Science Foundation of China(No.81974355 and No.82172525)a Hubei Province Technology Innovation Major Special Project(No.2018AAA067).
文摘As modern science and technology constantly progresses,the fields of artificial intelligence,mixed reality technology,remote technology,etc.have rapidly developed.Meanwhile,these technologies have been gradually applied to the medical field,leading to the development of intelligent medicine.What’s more,intelligent medicine has greatly promoted the development of traditional Chinese medicine(TCM),causing huge changes in the diagnosis of TCM ailments,remote treatment,teaching,etc.Therefore,there are both opportunities and challenges for inheriting and developing TCM.Herein,the related research progress of intelligent medicine in the TCM in China and abroad over the years is analyzed,with the purpose of introducing the present application status of intelligent medicine in TCM and providing reference for the inheritance and development of TCM in a new era.
基金supported by the National Natural Science Foundation of China(No.81974355 and No.82172525).
文摘Objective:To explore a new artificial intelligence(AI)-aided method to assist the clinical diagnosis of tibial plateau fractures(TPFs)and further measure its validity and feasibility.Methods:A total of 542 X-rays of TPFs were collected as a reference database.An AI algorithm(RetinaNet)was trained to analyze and detect TPF on the X-rays.The ability of the AI algorithm was determined by indexes such as detection accuracy and time taken for analysis.The algorithm performance was also compared with orthopedic physicians.Results:The AI algorithm showed a detection accuracy of 0.91 for the identification of TPF,which was similar to the performance of orthopedic physicians(0.92±0.03).The average time spent for analysis of the AI was 0.56 s,which was 16 times faster than human performance(8.44±3.26 s).Conclusion:The AI algorithm is a valid and efficient method for the clinical diagnosis of TPF.It can be a useful assistant for orthopedic physicians,which largely promotes clinical workflow and further guarantees the health and security of patients.