Artificial Intelligence-Based Prediction Of Recurrence After Endoscopic Dacryocystorhinostomy: A Narrative Review

Abstract

Postoperative recurrence remains a clinically significant limitation of endoscopic dacryocystorhinostomy (EDCR). This narrative review synthesizes current evidence on artificial intelligence (AI) and machine learning (ML) applications for surgical outcome prediction in ophthalmology and otolaryngology, and outlines a methodological framework — combining preoperative CT-based anatomical features with clinical variables — for the future development of an interpretable, externally validated AI-based recurrence-prediction model for EDCR.

Keywords:

Endoscopic dacryocystorhinostomy, recurrence, artificial intelligence

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