AI-Powered Eyecare Model Demonstrates Clinical Benefit in Randomized Trial
GUANGZHOU, CHINA – A novel artificial intelligence foundation model designed to assist clinicians in ophthalmology has shown promising results in a randomized controlled trial, potentially revolutionizing the diagnosis and treatment of eye diseases. The study,involving a vast collaborative effort across multiple international institutions,indicates the model can considerably aid in clinical decision-making,offering a pathway to improved patient outcomes and reduced burdens on healthcare systems globally.
Millions worldwide suffer from vision impairment, with conditions like diabetic retinopathy, glaucoma, and age-related macular degeneration posing critically important challenges to early detection and effective management. This new AI model aims to address these challenges by providing clinicians with a powerful tool for analyzing complex ophthalmic data,accelerating diagnosis,and personalizing treatment plans.The research team anticipates this technology will be notably impactful in regions with limited access to specialized ophthalmological expertise.
the project was conceived and supervised by T.Y. Wu and B. Shen. The study design was a collaborative effort led by T.Y. Wu,B. Shen, Yilan Wu, Z. Guo, D.Zhang, and Y.F. Zhao. B. Qian, Y. Qin, and P. Zhang spearheaded the development of the deep learning algorithm and its computational framework. Initial manuscript drafting involved contributions from T.Y. Wu, Yilan Wu, B. Qian, T. Li, Y. Qin,Z. Guo,D. zhang, and Y.F. Zhao.
Extensive data collection was facilitated by Y. Jiang, P. Zhang, Y. Zhou, Q. peng, C. Yu, J. Sun, A. Gupta, M.G.-B., M. Guo,A. Sharma, W. shi, L.Zhang, and You Wu.A broad spectrum of researchers – including S.Ma, R. Rao, B.S. Tan, J.A. O’Neill, T.A. Khan, H. Li, Y. Jiang, A.R. rad,D. Yu, Z. Ma, D. Wang, Y. Chen, W. Yang, R.Das,X. Zhao, C. Zhang, X. wang, Y. Chen, Q. Wang, H. Xu, S.K.H.S., J.Y.Y.C., V.T.T.C., H.-T. xu, R. Wu, J. Lu,Shan Lin,Z. Xu, N. Gupta, J. Evans, A. Lee, F. Diaz, MA., P. Costa, T.A. Moore, Y. Han, Y. Zhou, Shiqun Lin, X. Bai, J. Wang, X. Yang,H. Zhang, Y. Li, B.Qu, H. Yu, M. Guo, M. Zhou, W. Shi,L.M. Skollerud, F. Peng, B.S.S.,A.A. Taleb, C.E.N.M., P. Varma, D. Singh, A.K. Tripathi, D. Brown, U. Kumar, A. Khan, T. Ito, P.L.P. Wong, M.J.A., N.N. Amin, and I.E.-T. – participated in prospective validations.
Data collection and analysis within the randomized controlled trial were conducted by T. Chen, X. Zhang, Y. Han, X. Bai, J. Wang, X.Yang, H. Zhang, and Y. Li. Collaboration organization and critical manuscript revision were provided by J. Gao, P. Ren, S. Song, P.A. Kulkarni, L.-L.Lin, C.Y. Chen, G.S.W. Tan, Y.X.Wang, Y.-C. Tsai, C.-Y. Chen, Y.F. Zhao, B. Shen, and T.Y. Wu.All authors contributed critical feedback and approved the final manuscript.
