Objective： To construct a quantitative ethical evaluation index system for the clinical approval of medical technology in China. Methods： Exploratory factor analysis （EFA） and first-order confirmatory factor analy...Objective： To construct a quantitative ethical evaluation index system for the clinical approval of medical technology in China. Methods： Exploratory factor analysis （EFA） and first-order confirmatory factor analysis （CFA） based on a structure equation model （SEM）, higher-order CFA and normalisation were used to establish an ethical evaluation index system for the clinical approval of medical technology. Data were processed in SPSS 13.0 and Lisre 15.3. Results： There were 52 third class indices, 15 second class indices, and 3 first class indices in this ethical evaluation index system. The weight of each index was calculated by normalisation. Conclusion： This study developed a three-level ethical evaluation index system, comprising 70 indices, for the clinical approval of medical technology.展开更多
This paper explores the transformative impact of virtual worlds, augmented reality (AR), and the metaverse in the healthcare sector. It delves into the ways these technologies are reshaping patient care, medical educa...This paper explores the transformative impact of virtual worlds, augmented reality (AR), and the metaverse in the healthcare sector. It delves into the ways these technologies are reshaping patient care, medical education, and research, while also addressing the challenges and opportunities they present. The paper highlights the potential benefits of these technologies and emphasizes the need for comprehensive regulatory frameworks and ethical guidelines to ensure responsible integration. Finally it outlines their transformative impact and discusses the challenges and opportunities they present for the future of healthcare provision.展开更多
Artificial intelligence (AI) is rapidly being applied to a wide range of fields,including medicine,and has been considered as an approach that may augment or substitute human professionals in primary healthcare.Howeve...Artificial intelligence (AI) is rapidly being applied to a wide range of fields,including medicine,and has been considered as an approach that may augment or substitute human professionals in primary healthcare.However,AI also raises several challenges and ethical concerns.In this article,the author investigates and discusses three aspects of AI in medicine and healthcare:the application and promises of AI,special ethical concerns pertaining to AI in some frontier fields,and suggestive ethical governance systems.Despite great potentials of frontier AI research and development in the field of medical care,the ethical challenges induced by its applications has put forward new requirements for governance.To ensure “trustworthy” AI applications in healthcare and medicine,the creation of an ethical global governance framework and system as well as special guidelines for frontier AI applications in medicine are suggested.The most important aspects include the roles of governments in ethical auditing and the responsibilities of stakeholders in the ethical governance system.展开更多
作为推动社会进步与经济发展的重要力量,如何快速且精确地识别潜在颠覆性技术对于提升企业竞争力、推动产业变革等具有关键意义。本文提出一种融合专利数据与社交媒体数据的潜在颠覆性技术早期识别方法,是对已有研究理论和方法的重要补...作为推动社会进步与经济发展的重要力量,如何快速且精确地识别潜在颠覆性技术对于提升企业竞争力、推动产业变革等具有关键意义。本文提出一种融合专利数据与社交媒体数据的潜在颠覆性技术早期识别方法,是对已有研究理论和方法的重要补充。第一,检索相关领域专利数据,对数据进行划分;第二,基于颠覆性技术的特征,选取与颠覆性技术相关的指标以构建指标体系,并计算其技术影响力;第三,依托Bi-LSTM(bi-directional long short-termmemory)训练专利指标与技术影响力之间的关系,预测出候选颠覆性技术,并结合BERTopic提取技术主题;第四,通过BERTopic主题建模基于社交媒体数据提取出社会主题,并通过关注度和情感倾向对社会主题进行评价;第五,通过语义相似度,将社会主题与技术主题匹配映射,以对技术主题进行分类,进而识别出潜在颠覆性技术;第六,以医疗机器人为例,阐述该识别方法的应用过程。研究结果表明,Bi-LSTM模型在准确率、精准率、召回率和F1-score上均超过90%,优于其他模型;将医疗机器人领域中的潜在颠覆性技术划分为高关注度-积极态度、低关注度-积极态度与低关注度-消极态度3种类型;识别出的医疗机器人潜在颠覆性技术,能够为国家发展政策制定与相关产业布局提供参考。展开更多
基金Supported by National Natural Science Fundation of China(No.71173054)Guangdong Province Physiology and Social Science Fund(No.GD10CZX02)
文摘Objective： To construct a quantitative ethical evaluation index system for the clinical approval of medical technology in China. Methods： Exploratory factor analysis （EFA） and first-order confirmatory factor analysis （CFA） based on a structure equation model （SEM）, higher-order CFA and normalisation were used to establish an ethical evaluation index system for the clinical approval of medical technology. Data were processed in SPSS 13.0 and Lisre 15.3. Results： There were 52 third class indices, 15 second class indices, and 3 first class indices in this ethical evaluation index system. The weight of each index was calculated by normalisation. Conclusion： This study developed a three-level ethical evaluation index system, comprising 70 indices, for the clinical approval of medical technology.
文摘This paper explores the transformative impact of virtual worlds, augmented reality (AR), and the metaverse in the healthcare sector. It delves into the ways these technologies are reshaping patient care, medical education, and research, while also addressing the challenges and opportunities they present. The paper highlights the potential benefits of these technologies and emphasizes the need for comprehensive regulatory frameworks and ethical guidelines to ensure responsible integration. Finally it outlines their transformative impact and discusses the challenges and opportunities they present for the future of healthcare provision.
文摘Artificial intelligence (AI) is rapidly being applied to a wide range of fields,including medicine,and has been considered as an approach that may augment or substitute human professionals in primary healthcare.However,AI also raises several challenges and ethical concerns.In this article,the author investigates and discusses three aspects of AI in medicine and healthcare:the application and promises of AI,special ethical concerns pertaining to AI in some frontier fields,and suggestive ethical governance systems.Despite great potentials of frontier AI research and development in the field of medical care,the ethical challenges induced by its applications has put forward new requirements for governance.To ensure “trustworthy” AI applications in healthcare and medicine,the creation of an ethical global governance framework and system as well as special guidelines for frontier AI applications in medicine are suggested.The most important aspects include the roles of governments in ethical auditing and the responsibilities of stakeholders in the ethical governance system.
文摘作为推动社会进步与经济发展的重要力量,如何快速且精确地识别潜在颠覆性技术对于提升企业竞争力、推动产业变革等具有关键意义。本文提出一种融合专利数据与社交媒体数据的潜在颠覆性技术早期识别方法,是对已有研究理论和方法的重要补充。第一,检索相关领域专利数据,对数据进行划分;第二,基于颠覆性技术的特征,选取与颠覆性技术相关的指标以构建指标体系,并计算其技术影响力;第三,依托Bi-LSTM(bi-directional long short-termmemory)训练专利指标与技术影响力之间的关系,预测出候选颠覆性技术,并结合BERTopic提取技术主题;第四,通过BERTopic主题建模基于社交媒体数据提取出社会主题,并通过关注度和情感倾向对社会主题进行评价;第五,通过语义相似度,将社会主题与技术主题匹配映射,以对技术主题进行分类,进而识别出潜在颠覆性技术;第六,以医疗机器人为例,阐述该识别方法的应用过程。研究结果表明,Bi-LSTM模型在准确率、精准率、召回率和F1-score上均超过90%,优于其他模型;将医疗机器人领域中的潜在颠覆性技术划分为高关注度-积极态度、低关注度-积极态度与低关注度-消极态度3种类型;识别出的医疗机器人潜在颠覆性技术,能够为国家发展政策制定与相关产业布局提供参考。
