Artificial intelligence in oculoplasty: Current applications and future perspectives

Vollständiger Abstract

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Artificial intelligence (AI) is rapidly transforming clinical ophthalmology, with most validated applications in retinal and corneal imaging. In contrast, oculoplastic surgery – which encompasses eyelid, orbital, lacrimal, and periocular disorders – has only recently begun to incorporate AI into clinical workflows. Emerging applications include automated image analysis for eyelid malpositions, deep learning-based interpretation of orbital imaging, AI-assisted planning for dacryocystorhinostomy, and predictive modeling in reconstructive and aesthetic procedures. Despite encouraging results, challenges such as limited datasets, imaging heterogeneity, lack of multimodal integration, and regulatory readiness continue to hinder widespread clinical adoption. This mini-review summarizes current AI applications in oculoplastic surgery, identifies key knowledge gaps, and discusses future directions toward personalized, multimodal, AI-driven surgical care.