The primary objectives of medical safety education are to provide the public with essential knowledge about medications and to foster a scientific approach to drug usage.The era of using artificial intelligence to rev...The primary objectives of medical safety education are to provide the public with essential knowledge about medications and to foster a scientific approach to drug usage.The era of using artificial intelligence to revolutionize medical safety education has already dawned,and ChatGPT and other generative artificial intelligence models have immense potential in this domain.Notably,they offer a wealth of knowledge,anonymity,continuous availability,and personalized services.However,the practical implementation of generative artificial intelligence models such as ChatGPT in medical safety education still faces several challenges,including concerns about the accuracy of information,legal responsibilities,and ethical obligations.Moving forward,it is crucial to intelligently upgrade ChatGPT by leveraging the strengths of existing medical practices.This task involves further integrating the model with real-life scenarios and proactively addressing ethical and security issues with the ultimate goal of providing the public with comprehensive,convenient,efficient,and personalized medical services.展开更多
BACKGROUND Artificial intelligence(AI)is a branch of computer science that allows machines to analyze large datasets,learn from patterns,and perform tasks that would otherwise require human intelligence and supervisio...BACKGROUND Artificial intelligence(AI)is a branch of computer science that allows machines to analyze large datasets,learn from patterns,and perform tasks that would otherwise require human intelligence and supervision.It is an emerging tool in pediatric orthopedic surgery,with various promising applications.An evaluation of the current awareness and perceptions among pediatric orthopedic surgeons is necessary to facilitate AI utilization and highlight possible areas of concern.AIM To assess the awareness and perceptions of AI among pediatric orthopedic surgeons.METHODS This cross-sectional observational study was conducted using a structured questionnaire designed using QuestionPro online survey software to collect quantitative and qualitative data.One hundred and twenty-eight pediatric orthopedic surgeons affiliated with two groups:Pediatric Orthopedic Chapter of Saudi Orthopedics Association and Middle East Pediatric Orthopedic Society in Gulf Cooperation Council Countries were surveyed.RESULTS The pediatric orthopedic surgeons surveyed had a low level of familiarity with AI,with more than 60%of respondents rating themselves as being slightly familiar or not at all familiar.The most positively rated aspect of AI applications for pediatric orthopedic surgery was their ability to save time and enhance productivity,with 61.97%agreeing or strongly agreeing,and only 4.23%disagreeing or strongly disagreeing.Our participants also placed a high priority on patient privacy and data security,with over 90%rating them as quite important or highly important.Additional bivariate analyses suggested that physicians with a higher awareness of AI also have a more positive perception.CONCLUSION Our study highlights a lack of familiarity among pediatric orthopedic surgeons towards AI,and suggests a need for enhanced education and regulatory frameworks to ensure the safe adoption of AI.展开更多
To build towards expertise, one has to accept to modify his way of practicing, including： （1） a need to reflect on and about the action; （2） a continuous concern about our competence to practice; （3） tireless e...To build towards expertise, one has to accept to modify his way of practicing, including： （1） a need to reflect on and about the action; （2） a continuous concern about our competence to practice; （3） tireless effort to combine metacognition and mental practice in a trans-disciplinary approach; （4） adding research with neuroscience, understanding neuroplasticity, modulation and artificial intelligence. Usual practice actually does not include a continuous concern for CME （continued medical education） and is intermittent at best. This new paradigm constitutes the basis of our approach. Expertise starting in 2015 is described as an asymptotic curve unable to be obtained with usual practice and intermittent education. We suggest a new way of conceiving CME combining practice, reflection on action and in-situ simulation laboratory near work. We are describing TEE （technology-enhanced education） coupled with certain neuro-enhancers to achieve a break in the asymptotic curve of expertise. This is in reality a new conception of CME in medicine.展开更多
Artificial intelligence can effectively improve the efficiency and accuracy of medical diagnosis,clinical data analysis,medical image recognition,treatment plan decision-making,etc.It has broad application prospects i...Artificial intelligence can effectively improve the efficiency and accuracy of medical diagnosis,clinical data analysis,medical image recognition,treatment plan decision-making,etc.It has broad application prospects in the ophthalmic diagnosis,treatment,and nursing industry.However,the application of artificial intelligence in the ophthalmic diagnosis and nursing industry in China started relatively late,and there are insufficient ophthalmic diagnosis and nursing personnel who are familiar with artificial intelligence technologies.In order to promote the modernization of ophthalmic medicine in China and accelerate the development of a high-quality and modern medical education system,it is necessary to train a new generation of compound ophthalmic medical talents who are skilled in artificial intelligence and develop an advanced talent training model that meets the needs of the ophthalmic profession and the society.Based on the application status and development prospects of artificial intelligence in the ophthalmology industry,this paper analyzes the current medical education model in ophthalmology,examines the path of cultivating compound talents in ophthalmic diagnosis,treatment,and nursing,as well as proposes suggestions for developing a high-quality and modern medical education system.展开更多
人工智能及大数据已经成为包括医学教育在内的各研究领域的热点问题。为了阐明人工智能在医学教育中的发展趋势,利用CiteSpace软件分析2013-2022年Web of Science核心合集文献270篇。从发文量、国家和地区、研究机构、作者、发表杂志、...人工智能及大数据已经成为包括医学教育在内的各研究领域的热点问题。为了阐明人工智能在医学教育中的发展趋势,利用CiteSpace软件分析2013-2022年Web of Science核心合集文献270篇。从发文量、国家和地区、研究机构、作者、发表杂志、引文情况、关键词及发展趋势等方面进行综合分析得出研究结论:从2018年开始相关论文呈明显增长趋势,Mayo Clinic(梅奥诊所)成为全球发文量最多的研究机构;Friedman等形成了较为完整的研究团体;JAMA成为最高被引杂志;近年医学教育的人工智能应用研究热点问题主要集中在医学影像及虚拟手术等方面。展开更多
运用文献计量学方法,基于近10年来Web of Science(WoS)数据库中的人工智能医学教育应用研究相关文献,开展关联、聚类、突变等可视化分析,探究国际人工智能医学教育应用研究现状、研究热点和发展趋势,发现机器人辅助手术培训、智能评价...运用文献计量学方法,基于近10年来Web of Science(WoS)数据库中的人工智能医学教育应用研究相关文献,开展关联、聚类、突变等可视化分析,探究国际人工智能医学教育应用研究现状、研究热点和发展趋势,发现机器人辅助手术培训、智能评价反馈系统和智能虚拟仿真系统是国际人工智能医学教育的研究热点,其研究演进遵循从标准化到个性化、从实体空间到虚实融合、从关注独立思考到人机协同决策这一脉络,以期为我国人工智能医学教育研究工作者提供参考和情报支持。展开更多
目的构建一种基于人工智能大语言模型(large language model,LLM)技术、可用于医学教育的新型虚拟患者(virtual patient,VP)系统,评价该系统在基层医生进修学习全科医学临床思维中的应用效果。方法选取2021年1月至2024年2月在东南大学...目的构建一种基于人工智能大语言模型(large language model,LLM)技术、可用于医学教育的新型虚拟患者(virtual patient,VP)系统,评价该系统在基层医生进修学习全科医学临床思维中的应用效果。方法选取2021年1月至2024年2月在东南大学附属中大医院进修的基层社区医生为研究对象,随机分为试验组和对照组,分别采用基于LLM的VP系统教学、传统教学方法进行授课,通过临床思维理论知识考核、临床思维能力考核、课程满意度调查评估教学效果,并对结果进行相应的统计学分析。结果共纳入124名基层社区医生,其中试验组60例、对照组64例,两组在一般基线资料上差异无统计学意义,具有可比性。课程结束后,试验组临床思维理论知识考核成绩显著高于对照组(83.83±3.15 vs.79.92±4.52,P<0.01),且不及格率显著低于对照组(0.00%vs.9.38%,P<0.05);试验组在临床思维能力3个维度(批判性、系统性、循证思维)方面教学后分数均显著高于教学前,而对照组仅在批判性思维维度上教学前后差异有统计学意义;教学后试验组在系统思维、循证思维方面分数均显著高于对照组(P<0.05),但在批判性思维上两组分数差异无统计学意义。试验组对授课的总体满意度也显著高于对照组(93.33%vs.85.48%,P<0.05)。结论基于LLM的VP系统提升了学员对临床思维理论知识的掌握程度,也促进了其临床思维能力的培养,该教学方法可为其他医学教育群体提供新的教学工具和思路。展开更多
随着人工智能技术的快速发展,其在医学教育领域的应用逐渐深入。CIPP(context input process product,CIPP)理论作为一种综合性的教学设计和评价模型,为AI技术在医学教学评价中的应用提供了理论基础。该研究旨在探讨AI如何基于CIPP理论...随着人工智能技术的快速发展,其在医学教育领域的应用逐渐深入。CIPP(context input process product,CIPP)理论作为一种综合性的教学设计和评价模型,为AI技术在医学教学评价中的应用提供了理论基础。该研究旨在探讨AI如何基于CIPP理论赋能医学教学评价,深入分析背景、输入、过程和结果四个方面,分析AI在不同阶段的应用实践,并讨论AI在赋能医学教学评价中面临的挑战、问题,以及未来发展趋势。展开更多
文摘The primary objectives of medical safety education are to provide the public with essential knowledge about medications and to foster a scientific approach to drug usage.The era of using artificial intelligence to revolutionize medical safety education has already dawned,and ChatGPT and other generative artificial intelligence models have immense potential in this domain.Notably,they offer a wealth of knowledge,anonymity,continuous availability,and personalized services.However,the practical implementation of generative artificial intelligence models such as ChatGPT in medical safety education still faces several challenges,including concerns about the accuracy of information,legal responsibilities,and ethical obligations.Moving forward,it is crucial to intelligently upgrade ChatGPT by leveraging the strengths of existing medical practices.This task involves further integrating the model with real-life scenarios and proactively addressing ethical and security issues with the ultimate goal of providing the public with comprehensive,convenient,efficient,and personalized medical services.
文摘BACKGROUND Artificial intelligence(AI)is a branch of computer science that allows machines to analyze large datasets,learn from patterns,and perform tasks that would otherwise require human intelligence and supervision.It is an emerging tool in pediatric orthopedic surgery,with various promising applications.An evaluation of the current awareness and perceptions among pediatric orthopedic surgeons is necessary to facilitate AI utilization and highlight possible areas of concern.AIM To assess the awareness and perceptions of AI among pediatric orthopedic surgeons.METHODS This cross-sectional observational study was conducted using a structured questionnaire designed using QuestionPro online survey software to collect quantitative and qualitative data.One hundred and twenty-eight pediatric orthopedic surgeons affiliated with two groups:Pediatric Orthopedic Chapter of Saudi Orthopedics Association and Middle East Pediatric Orthopedic Society in Gulf Cooperation Council Countries were surveyed.RESULTS The pediatric orthopedic surgeons surveyed had a low level of familiarity with AI,with more than 60%of respondents rating themselves as being slightly familiar or not at all familiar.The most positively rated aspect of AI applications for pediatric orthopedic surgery was their ability to save time and enhance productivity,with 61.97%agreeing or strongly agreeing,and only 4.23%disagreeing or strongly disagreeing.Our participants also placed a high priority on patient privacy and data security,with over 90%rating them as quite important or highly important.Additional bivariate analyses suggested that physicians with a higher awareness of AI also have a more positive perception.CONCLUSION Our study highlights a lack of familiarity among pediatric orthopedic surgeons towards AI,and suggests a need for enhanced education and regulatory frameworks to ensure the safe adoption of AI.
文摘To build towards expertise, one has to accept to modify his way of practicing, including： （1） a need to reflect on and about the action; （2） a continuous concern about our competence to practice; （3） tireless effort to combine metacognition and mental practice in a trans-disciplinary approach; （4） adding research with neuroscience, understanding neuroplasticity, modulation and artificial intelligence. Usual practice actually does not include a continuous concern for CME （continued medical education） and is intermittent at best. This new paradigm constitutes the basis of our approach. Expertise starting in 2015 is described as an asymptotic curve unable to be obtained with usual practice and intermittent education. We suggest a new way of conceiving CME combining practice, reflection on action and in-situ simulation laboratory near work. We are describing TEE （technology-enhanced education） coupled with certain neuro-enhancers to achieve a break in the asymptotic curve of expertise. This is in reality a new conception of CME in medicine.
文摘Artificial intelligence can effectively improve the efficiency and accuracy of medical diagnosis,clinical data analysis,medical image recognition,treatment plan decision-making,etc.It has broad application prospects in the ophthalmic diagnosis,treatment,and nursing industry.However,the application of artificial intelligence in the ophthalmic diagnosis and nursing industry in China started relatively late,and there are insufficient ophthalmic diagnosis and nursing personnel who are familiar with artificial intelligence technologies.In order to promote the modernization of ophthalmic medicine in China and accelerate the development of a high-quality and modern medical education system,it is necessary to train a new generation of compound ophthalmic medical talents who are skilled in artificial intelligence and develop an advanced talent training model that meets the needs of the ophthalmic profession and the society.Based on the application status and development prospects of artificial intelligence in the ophthalmology industry,this paper analyzes the current medical education model in ophthalmology,examines the path of cultivating compound talents in ophthalmic diagnosis,treatment,and nursing,as well as proposes suggestions for developing a high-quality and modern medical education system.
文摘人工智能及大数据已经成为包括医学教育在内的各研究领域的热点问题。为了阐明人工智能在医学教育中的发展趋势,利用CiteSpace软件分析2013-2022年Web of Science核心合集文献270篇。从发文量、国家和地区、研究机构、作者、发表杂志、引文情况、关键词及发展趋势等方面进行综合分析得出研究结论:从2018年开始相关论文呈明显增长趋势,Mayo Clinic(梅奥诊所)成为全球发文量最多的研究机构;Friedman等形成了较为完整的研究团体;JAMA成为最高被引杂志;近年医学教育的人工智能应用研究热点问题主要集中在医学影像及虚拟手术等方面。
文摘运用文献计量学方法,基于近10年来Web of Science(WoS)数据库中的人工智能医学教育应用研究相关文献,开展关联、聚类、突变等可视化分析,探究国际人工智能医学教育应用研究现状、研究热点和发展趋势,发现机器人辅助手术培训、智能评价反馈系统和智能虚拟仿真系统是国际人工智能医学教育的研究热点,其研究演进遵循从标准化到个性化、从实体空间到虚实融合、从关注独立思考到人机协同决策这一脉络,以期为我国人工智能医学教育研究工作者提供参考和情报支持。
文摘目的构建一种基于人工智能大语言模型(large language model,LLM)技术、可用于医学教育的新型虚拟患者(virtual patient,VP)系统,评价该系统在基层医生进修学习全科医学临床思维中的应用效果。方法选取2021年1月至2024年2月在东南大学附属中大医院进修的基层社区医生为研究对象,随机分为试验组和对照组,分别采用基于LLM的VP系统教学、传统教学方法进行授课,通过临床思维理论知识考核、临床思维能力考核、课程满意度调查评估教学效果,并对结果进行相应的统计学分析。结果共纳入124名基层社区医生,其中试验组60例、对照组64例,两组在一般基线资料上差异无统计学意义,具有可比性。课程结束后,试验组临床思维理论知识考核成绩显著高于对照组(83.83±3.15 vs.79.92±4.52,P<0.01),且不及格率显著低于对照组(0.00%vs.9.38%,P<0.05);试验组在临床思维能力3个维度(批判性、系统性、循证思维)方面教学后分数均显著高于教学前,而对照组仅在批判性思维维度上教学前后差异有统计学意义;教学后试验组在系统思维、循证思维方面分数均显著高于对照组(P<0.05),但在批判性思维上两组分数差异无统计学意义。试验组对授课的总体满意度也显著高于对照组(93.33%vs.85.48%,P<0.05)。结论基于LLM的VP系统提升了学员对临床思维理论知识的掌握程度,也促进了其临床思维能力的培养,该教学方法可为其他医学教育群体提供新的教学工具和思路。
文摘随着人工智能技术的快速发展,其在医学教育领域的应用逐渐深入。CIPP(context input process product,CIPP)理论作为一种综合性的教学设计和评价模型,为AI技术在医学教学评价中的应用提供了理论基础。该研究旨在探讨AI如何基于CIPP理论赋能医学教学评价,深入分析背景、输入、过程和结果四个方面,分析AI在不同阶段的应用实践,并讨论AI在赋能医学教学评价中面临的挑战、问题,以及未来发展趋势。
