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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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Principais autores: 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
Sprog:Inglês
Udgivet: Nature Portfolio 2025-04-01
Serier:Scientific Reports
Fag:
Dry eye
Meibomian gland dysfunction
Lifestyle
Artificial intelligence
Machine learning
Age
Online adgang:https://doi.org/10.1038/s41598-025-96778-x
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