Artificial intelligence models utilize lifestyle factors to predict dry eye related outcomes

Abstract The purpose of this study is to examine and interpret machine learning models that predict dry eye (DE)-related clinical signs, subjective symptoms, and clinician diagnoses by heavily weighting lifestyle factors in the predictions. Machine learning models were trained to take clinical asses...

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Autors principals:	Andrew D. Graham, Jiayun Wang, Tejasvi Kothapalli, Jennifer E. Ding, Helen Tasho, Alisa Molina, Vivien Tse, Sarah M. Chang, Stella X. Yu, Meng C. Lin
Format:	Artigo
Idioma:	Inglês
Publicat:	Nature Portfolio 2025-04-01
Col·lecció:	Scientific Reports
Matèries:	Dry eye Meibomian gland dysfunction Lifestyle Artificial intelligence Machine learning Age
Accés en línia:	https://doi.org/10.1038/s41598-025-96778-x
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