Kyle Alexander Bolo

Kyle Bolo, MD, is a clinician scientist and glaucoma specialist at the USC Roski Eye Institute, part of Keck Medicine of USC. He diagnoses and treats patients for a variety of eye diseases and has extensive expertise treating glaucoma and performing cataract surgery. Dr. Bolo conducts research at the interface of population eye health, bioinformatics, and machine learning. His priorities include investigating the impact of glaucoma on different patient populations and health systems, understanding the effects of glaucoma screening, and modernizing the detection and care of those with and at risk for glaucoma using data-driven and machine learning tools. His work advances a shared focus for promoting reproducible data science research.Dr. Bolo is also helping to educate the next generation of physicians. He is an assistant professor of ophthalmology at the Keck School of Medicine of USC.

• NIH/SC-CTSI: Mentored Career Development Award in Clinical and Translational Science, 2026-2029
• American Glaucoma Society: Mentoring for Advancement of Physician-Scientists (MAPS) Award, 2025-2026
• Columbia University: Albert B. Knapp Scholarship, 2019
• Columbia University: Alpha Omega Alpha, 2018

• Safety of Pharmacologic Dilation: Incidence and Risk Factors of Acute Angle Closure in a Nationwide Cohort. Am J Ophthalmol. 2026 Mar; 283:138-148.. View in PubMed
• Comparison of RETFound and a Supervised Convolutional Neural Network for Detection of Referable Glaucoma from Fundus Photographs. Ophthalmol Sci. 2026 Feb; 6(2):101008.. View in PubMed
• OpenAI o1 Large Language Model Outperforms GPT-4o, Gemini 1.5 Flash, and Human Test Takers on Ophthalmology Board-Style Questions. Ophthalmol Sci. 2025 Nov-Dec; 5(6):100844.. View in PubMed
• Acute Angle Closure Incidence in a Large Countywide Safety Net Teleretinal Screening Program. JAMA Ophthalmol. 2025 Nov 01; 143(11):883-890.. View in PubMed
• Comparison of Foundation and Supervised Learning-Based Models for Detection of Referable Glaucoma from Fundus Photographs. medRxiv. 2025 Aug 24.. View in PubMed
• A comparative analysis of DeepSeek R1, DeepSeek-R1-Lite, OpenAi o1 Pro, and Grok 3 performance on ophthalmology board-style questions. Sci Rep. 2025 Jul 02; 15(1):23101.. View in PubMed
• Comparison of Deep Learning and Clinician Performance for Detecting Referable Glaucoma from Fundus Photographs in a Safety Net Population. Ophthalmol Sci. 2025 Jul-Aug; 5(4):100751.. View in PubMed
• Applications of deep learning in the analysis of optical coherence tomography images for glaucoma-related diagnostics. Taiwan J Ophthalmol. 2025; 15(3):354-363.. View in PubMed
• Analysis of ChatGPT Responses to Ophthalmic Cases: Can ChatGPT Think like an Ophthalmologist? Ophthalmol Sci. 2025 Jan-Feb; 5(1):100600.. View in PubMed
• Automated expert-level scleral spur detection and quantitative biometric analysis on the ANTERION anterior segment OCT system. Br J Ophthalmol. 2024 05 21; 108(5):702-709.. View in PubMed
• Steps to Measurement Floor of an Optical Microangiography Device in Glaucoma. Am J Ophthalmol. 2021 11; 231:58-69.. View in PubMed
• Broad internal limiting membrane peeling with adjunctive plasma-thrombin for repair of large macular holes : A retrospective case series. Eur J Ophthalmol. 2021 May; 31(3):1338-1344.. View in PubMed
• Attenuation of Inherited and Acquired Retinal Degeneration Progression with Gene-based Techniques. Mol Diagn Ther. 2019 02; 23(1):113-120.. View in PubMed

• Xu, Benjamin
• Humayun, Mark
• Moshfeghi, Andrew
• Shahidi, Mahnaz