AI-Based Advanced Approaches and Dry Eye Disease Detection Based on Multi-Source Evidence: Cases, Applications, Issues, and Future Directions

This study explores the potential of Artificial Intelligence (AI) in early screening and prognosis of Dry Eye Disease (DED), aiming to enhance the accuracy of therapeutic approaches for eye-care practitioners. Despite the promising opportunities, challenges such as diverse diagnostic evidence, compl...

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Bibliographic Details

Published in:	Big Data Mining and Analytics
Main Authors:	Mini Han Wang, Lumin Xing, Yi Pan, Feng Gu, Junbin Fang, Xiangrong Yu, Chi Pui Pang, Kelvin Kam-Lung Chong, Carol Yim-Lui Cheung, Xulin Liao, Xiaoxiao Fang, Jie Yang, Ruoyu Zhou, Xiaoshu Zhou, Fengling Wang, Wenjian Liu
Format:	Article
Language:	English
Published:	Tsinghua University Press 2024-06-01
Subjects:	artificial intelligence (ai) dry eye disease (ded) detection ophthalmology multi-source evidence
Online Access:	https://www.sciopen.com/article/10.26599/BDMA.2023.9020024