A machine learning approach to predicting dry eye-related signs, symptoms and diagnoses from meibography images

Purpose: To use artificial intelligence to identify relationships between morphological characteristics of the Meibomian glands (MGs), subject factors, clinical outcomes, and subjective symptoms of dry eye. Methods: A total of 562 infrared meibography images were collected from 363 subjects (170 con...

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Autori principali:	Andrew D. Graham, Tejasvi Kothapalli, Jiayun Wang, Jennifer Ding, Vivien Tse, Penny A. Asbell, Stella X. Yu, Meng C. Lin
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2024-09-01
Serie:	Heliyon
Soggetti:	Machine learning Artificial intelligence Meibography Meibomian gland morphology Dry eye Meibomian gland dysfunction
Accesso online:	http://www.sciencedirect.com/science/article/pii/S240584402412052X
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