Latest developments of generative artificial intelligence and applications in ophthalmology
Year: 2024
Type: article
Abstract: 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.
Institutions: Tsinghua University, Sun Yat-sen University, State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Beijing Tsinghua Chang Gung Hospital, The First Affiliated Hospital, Sun Yat-sen University, Johns Hopkins University, National University of Singapore, Singapore National Eye Center, Singapore Eye Research Institute, Duke-NUS Medical School, Stanford University, Hainan Eye Hospital, Chinese University of Hong Kong, Shenzhen
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,950
Funder: Tsinghua University
Award: G43951589
OpenAlex ID: W4401525975
