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- W4313585924 abstract "Artificial intelligence (AI) has been approved for biomedical research in diverse areas from bedside clinical studies to benchtop basic scientific research. For ophthalmic research, in particular glaucoma, AI applications are rapidly growing for potential clinical translation given the vast data available and the introduction of federated learning. Conversely, AI for basic science remains limited despite its useful power in providing mechanistic insight. In this perspective, we discuss recent progress, opportunities, and challenges in the application of AI in glaucoma for scientific discoveries. Specifically, we focus on the research paradigm of reverse translation, in which clinical data are first used for patient-centered hypothesis generation followed by transitioning into basic science studies for hypothesis validation. We elaborate on several distinctive areas of research opportunities for reverse translation of AI in glaucoma including disease risk and progression prediction, pathology characterization, and sub-phenotype identification. We conclude with current challenges and future opportunities for AI research in basic science for glaucoma such as inter-species diversity, AI model generalizability and explainability, as well as AI applications using advanced ocular imaging and genomic data." @default.
- W4313585924 created "2023-01-06" @default.
- W4313585924 creator A5010480125 @default.
- W4313585924 creator A5015084700 @default.
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- W4313585924 creator A5044200406 @default.
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- W4313585924 creator A5055560750 @default.
- W4313585924 creator A5081505316 @default.
- W4313585924 date "2023-01-04" @default.
- W4313585924 modified "2023-10-01" @default.
- W4313585924 title "Reverse translation of artificial intelligence in glaucoma: Connecting basic science with clinical applications" @default.
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