Lee, Aaron Y.

Artificial intelligence and deep learning in ophthalmology

Ting, D. S. W., Pasquale, L. R., Peng, L., Campbell, J. P., Lee, A. Y., Raman, R., Tan, G. S. W., Schmetterer, L., Keane, P. A., & Wong, T. Y. (2019) · British Journal of Ophthalmology

Retinal Imaging and AnalysisArtificial Intelligence in Healthcare and Education

Cited by 1,554

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension

Liu, X., Cruz Rivera, S., Moher, D., Calvert, M. J., Denniston, A. K., The SPIRIT-AI and CONSORT-AI Working Group, SPIRIT-AI and CONSORT-AI Steering Group, Chan, A.-W., Darzi, A., Holmes, C., et al. (2020) · Nature Medicine

Meta-analysis and systematic reviewsArtificial Intelligence in Healthcare and Education

Cited by 1,421

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

Vasey, B., Nagendran, M., Campbell, B., Clifton, D. A., Collins, G. S., Denaxas, S., Denniston, A. K., Faes, L., Geerts, B., Ibrahim, M., et al. (2022) · Nature Medicine

Artificial Intelligence in Healthcare and EducationMeta-analysis and systematic reviews

Cited by 1,039

A foundation model for generalizable disease detection from retinal images

Zhou, Y., Chia, M. A., Wagner, S. K., Ayhan, M. S., Williamson, D. J., Struyven, R. R., Liu, T., Xu, M., Lozano, M. G., Woodward-Court, P., et al. (2023) · Nature

Retinal Imaging and AnalysisOphthalmology and Visual Health Research

Cited by 1,014

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension

Cruz Rivera, S., Liu, X., Chan, A.-W., Denniston, A. K., Calvert, M. J., The SPIRIT-AI and CONSORT-AI Working Group, SPIRIT-AI and CONSORT-AI Steering Group, Darzi, A., Holmes, C., Yau, C., et al. (2020) · Nature Medicine

Meta-analysis and systematic reviewsArtificial Intelligence in Healthcare and Education

Cited by 933

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension

Liu, X., Cruz Rivera, S., Moher, D., Calvert, M. J., Denniston, A. K., Ashrafian, H., Beam, A. L., Chan, A.-W., Collins, G. S., Deeks, A. D. J., et al. (2020) · The Lancet Digital Health

Meta-analysis and systematic reviewsArtificial Intelligence in Healthcare and Education

Cited by 555

Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension

Cruz Rivera, S., Liu, X., Chan, A.-W., Denniston, A. K., Calvert, M. J., Ashrafian, H., Beam, A. L., Collins, G. S., Darzi, A., Deeks, J. J., et al. (2020) · The Lancet Digital Health

Meta-analysis and systematic reviewsArtificial Intelligence in Healthcare and Education

Cited by 486

Genome-wide association study of advanced age-related macular degeneration identifies a role of the hepatic lipase gene ( LIPC )

Neale, B. M., Fagerness, J., Reynolds, R., Sobrin, L., Parker, M., Raychaudhuri, S., Tan, P. L., Oh, E. C., Merriam, J. E., Souied, E., et al. (2010) · Proceedings of the National Academy of Sciences

Retinal Diseases and TreatmentsGenetic Associations and Epidemiology

Cited by 442

Prevalence of Diabetic Retinopathy in the US in 2021

Lundeen, E. A., Burke-Conte, Z., Rein, D. B., Wittenborn, J. S., Saaddine, J., Lee, A. Y., & Flaxman, A. D. (2023) · JAMA Ophthalmology

Retinal Diseases and TreatmentsRetinal Imaging and Analysis

Cited by 293

Automated Diabetic Retinopathy Image Assessment Software

Tufail, A., Rudisill, C., Egan, C., Kapetanakis, V. V., Salas-Vega, S., Owen, C. G., Lee, A., Louw, V., Anderson, J., Liew, G., et al. (2017) · Ophthalmology

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 283

Common variants near FRK/COL10A1 and VEGFA are associated with advanced age-related macular degeneration

Yu, Y., Bhangale, T. R., Fagerness, J., Ripke, S., Thorleifsson, G., Tan, P. L., Souied, E. H., Richardson, A. J., Merriam, J. E., Buitendijk, G. H. S., et al. (2011) · Human Molecular Genetics

Retinal Diseases and TreatmentsGenetic Associations and Epidemiology

Cited by 254

Clinical applications of continual learning machine learning

Lee, C. S., & Lee, A. Y. (2020) · The Lancet Digital Health

Domain Adaptation and Few-Shot LearningArtificial Intelligence in Healthcare and Education

Cited by 254

Multicenter, Head-to-Head, Real-World Validation Study of Seven Automated Artificial Intelligence Diabetic Retinopathy Screening Systems

Lee, A. Y., Yanagihara, R. T., Lee, C. S., Blazes, M., Jung, H. C., Chee, Y. E., Gencarella, M. D., Gee, H., Maa, A. Y., Cockerham, G. C., et al. (2021) · Diabetes Care

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 194

Association between cataract extraction and development of dementia

Lee, C. S., Gibbons, L. E., Lee, A. Y., Yanagihara, R. T., Blazes, M. S., Lee, M. L., McCurry, S. M., Bowen, J. D., McCormick, W. C., Crane, P. K., et al. (2022) · JAMA Internal Medicine

Dementia and Cognitive Impairment ResearchIntraocular Surgery and Lenses

Cited by 163

Large language models and their impact in ophthalmology

Betzler, B. K., Chen, H., Cheng, C.-Y., Lee, C. S., Ning, G., Song, S. J., Lee, A. Y., Kawasaki, R., van Wijngaarden, P., Grzybowski, A., et al. (2023) · The Lancet Digital Health

Artificial Intelligence in Healthcare and EducationOphthalmology and Visual Health Research

Cited by 161

Pharmacogenetics of complement factor H (Y402H) and treatment of exudative age-related macular degeneration with ranibizumab

Lee, A. Y., Raya, A. K., Kymes, S. M., Shiels, A., & Brantley, M. A. (2009) · British Journal of Ophthalmology

Retinal Diseases and TreatmentsOcular Diseases and Behçet’s Syndrome

Cited by 134

Federated Learning for Microvasculature Segmentation and Diabetic Retinopathy Classification of OCT Data

Lo, J., Yu, T. T., Ma, D., Zang, P., Owen, J. P., Zhang, Q., Wang, R. K., Beg, M. F., Lee, A. Y., Jia, Y., et al. (2021) · Ophthalmology Science

Retinal Imaging and AnalysisRetinal Diseases and Treatments

Cited by 105

Trustworthy AI: Closing the gap between development and integration of AI systems in ophthalmic practice

González-Gonzalo, C., Thee, E. F., Klaver, C. C. W., Lee, A. Y., Schlingemann, R. O., Tufail, A., Verbraak, F., & Sánchez, C. I. (2022) · Progress in Retinal and Eye Research

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 103

Protecting Data Privacy in the Age of AI-Enabled Ophthalmology

Tom, E., Keane, P. A., Blazes, M., Pasquale, L. R., Chiang, M. F., Lee, A. Y., Lee, C. S., & and AAO Artificial Intelligence Task Force (2020) · Translational Vision Science & Technology

Artificial Intelligence in Healthcare and EducationPrivacy-Preserving Technologies in Data

Cited by 92

Policy-Driven, Multimodal Deep Learning for Predicting Visual Fields from the Optic Disc and OCT Imaging

Kihara, Y., Montesano, G., Chen, A., Amerasinghe, N., Dimitriou, C., Jacob, A., Chabi, A., Crabb, D. P., & Lee, A. Y. (2022) · Ophthalmology

Glaucoma and retinal disordersRetinal Imaging and Analysis

Cited by 62

Deep learning algorithms to detect diabetic kidney disease from retinal photographs in multiethnic populations with diabetes

Betzler, B. K., Chee, E. Y. L., He, F., Lim, C. C., Ho, J., Hamzah, H., Tan, N. C., Liew, G., McKay, G. J., Hogg, R. E., et al. (2023) · Journal of the American Medical Informatics Association

Retinal Imaging and AnalysisChronic Kidney Disease and Diabetes

Cited by 42

Use of artificial intelligence with retinal imaging in screening for diabetes-associated complications: systematic review

Yang, Q., Bee, Y. M., Lim, C. C., Sabanayagam, C., Yim-Lui Cheung, C., Wong, T. Y., Ting, D. S. W., Lim, L.-L., Li, H., He, M., et al. (2025) · eClinicalMedicine

Retinal Imaging and AnalysisArtificial Intelligence in Healthcare

Cited by 38

Deep learning models for COVID-19 chest X-ray classification: preventing shortcut learning using feature Disentanglement

Trivedi, A., Robinson, C., Blazes, M., Ortiz, A., Desbiens, J., Gupta, S., Dodhia, R., Bhatraju, P. K., Liles, W. C., Kalpathy-Cramer, J., et al. (2022) · PLOS ONE

COVID-19 diagnosis using AIRadiomics and Machine Learning in Medical Imaging

Cited by 28

Diabetic retinopathy and dementia association, beyond diabetes severity

Lee, C. S., Krakauer, C., Su, Y.-R., Walker, R. L., Blazes, M., McCurry, S. M., Bowen, J. D., McCormick, W. C., Lee, A. Y., Boyko, E. J., et al. (2023) · American Journal of Ophthalmology

Dementia and Cognitive Impairment ResearchRetinal Diseases and Treatments

Cited by 25