aceThe Use of Artificial Intelligence to Predict Visual Outcome in Patients With Macular Pucker
Purpose: To assess the current role of artificial intelligence (AI) to predict postoperative best-corrected visual acuity (BCVA) after macular pucker surgery using optical coherence tomography (OCT) data. Methods: A systematic search was conducted of PubMed, EMBASE, Web of Science, Scopus, and the Cochrane Library. Data extraction included study design, demographics, AI model characteristics, and performance metrics. Study quality was assessed using the Prediction Model Risk of Bias Assessment + Artificial Intel…
Deep learning models applied to preoperative OCT scans predicted postoperative visual acuity after macular pucker surgery and outperformed human grading in the reviewed studies.
Clinical translation depends on model generalizability, interpretability, real-time application, and functional data, and the authors say multicenter validation is still needed.
Evidence
- Peer-reviewedJournal of VitreoRetinal Diseases2026-10-20
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Truvace Impact Record TRV-2026-2099, v1: “The Use of Artificial Intelligence to Predict Visual Outcome in Patients With Macular Pucker.” Truvace, 2026-10-21. /record/TRV-2026-2099 (accessed at citation time). sha256 c6ba8e22cbcb5c87…
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