Xiaoru Feng , Kezheng Xu , Ming-Jie Luo , Haichao Chen , Yangfan Yang , Qi He , Chenxin Song , Ruiyao Li , You Wu , Haibo Wang , Yih Chung Tham , Daniel Shu Wei Ting , Haotian Lin , Tien Yin Wong , Dennis Shun-chiu Lam
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It outlines the need for development of a standard framework for comprehensive assessments, robust evidence, and exploration of the potential of multimodal capabilities and intelligent agents. Additionally, the review addresses the risks in AI model development and application in clinical service and research of ophthalmology, including data privacy, data bias, adaptation friction, over interdependence, and job replacement, based on which we summarized a risk management framework to mitigate these concerns. This review highlights the transformative potential of generative AI in enhancing patient care, improving operational efficiency in the clinical service and research in ophthalmology. It also advocates for a balanced approach to its adoption.</p></div>","PeriodicalId":8594,"journal":{"name":"Asia-Pacific Journal of Ophthalmology","volume":"13 4","pages":"Article 100090"},"PeriodicalIF":3.7000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2162098924000914/pdfft?md5=d7ea0e26c3fa992ee3c0a0c2b8d57bdc&pid=1-s2.0-S2162098924000914-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Latest developments of generative artificial intelligence and applications in ophthalmology\",\"authors\":\"Xiaoru Feng , Kezheng Xu , Ming-Jie Luo , Haichao Chen , Yangfan Yang , Qi He , Chenxin Song , Ruiyao Li , You Wu , Haibo Wang , Yih Chung Tham , Daniel Shu Wei Ting , Haotian Lin , Tien Yin Wong , Dennis Shun-chiu Lam\",\"doi\":\"10.1016/j.apjo.2024.100090\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The emergence of generative artificial intelligence (AI) has revolutionized various fields. In ophthalmology, generative AI has the potential to enhance efficiency, accuracy, personalization and innovation in clinical practice and medical research, through processing data, streamlining medical documentation, facilitating patient-doctor communication, aiding in clinical decision-making, and simulating clinical trials. This review focuses on the development and integration of generative AI models into clinical workflows and scientific research of ophthalmology. It outlines the need for development of a standard framework for comprehensive assessments, robust evidence, and exploration of the potential of multimodal capabilities and intelligent agents. Additionally, the review addresses the risks in AI model development and application in clinical service and research of ophthalmology, including data privacy, data bias, adaptation friction, over interdependence, and job replacement, based on which we summarized a risk management framework to mitigate these concerns. 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Latest developments of generative artificial intelligence and applications in ophthalmology
The emergence of generative artificial intelligence (AI) has revolutionized various fields. In ophthalmology, generative AI has the potential to enhance efficiency, accuracy, personalization and innovation in clinical practice and medical research, through processing data, streamlining medical documentation, facilitating patient-doctor communication, aiding in clinical decision-making, and simulating clinical trials. This review focuses on the development and integration of generative AI models into clinical workflows and scientific research of ophthalmology. It outlines the need for development of a standard framework for comprehensive assessments, robust evidence, and exploration of the potential of multimodal capabilities and intelligent agents. Additionally, the review addresses the risks in AI model development and application in clinical service and research of ophthalmology, including data privacy, data bias, adaptation friction, over interdependence, and job replacement, based on which we summarized a risk management framework to mitigate these concerns. This review highlights the transformative potential of generative AI in enhancing patient care, improving operational efficiency in the clinical service and research in ophthalmology. It also advocates for a balanced approach to its adoption.
期刊介绍:
The Asia-Pacific Journal of Ophthalmology, a bimonthly, peer-reviewed online scientific publication, is an official publication of the Asia-Pacific Academy of Ophthalmology (APAO), a supranational organization which is committed to research, training, learning, publication and knowledge and skill transfers in ophthalmology and visual sciences. The Asia-Pacific Journal of Ophthalmology welcomes review articles on currently hot topics, original, previously unpublished manuscripts describing clinical investigations, clinical observations and clinically relevant laboratory investigations, as well as .perspectives containing personal viewpoints on topics with broad interests. Editorials are published by invitation only. Case reports are generally not considered. The Asia-Pacific Journal of Ophthalmology covers 16 subspecialties and is freely circulated among individual members of the APAO’s member societies, which amounts to a potential readership of over 50,000.