Unsupervised Learning Based on Meibography Enables Subtyping of Dry Eye Disease and Reveals Ocular Surface Features

PURPOSE: This study aimed to establish an image-based classification that can reveal the clinical characteristics of patients with dry eye using unsupervised learning methods. METHODS: In this study, we analyzed 82,236 meibography images from 20,559 subjects. Using the SimCLR neural network, the ima...

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Detalles Bibliográficos
Autores principales: Li, Siyan, Wang, Yiyi, Yu, Chunyu, Li, Qiyuan, Chang, Pingjun, Wang, Dandan, Li, Zhangliang, Zhao, Yinying, Zhang, Hongfang, Tang, Ning, Guan, Weichen, Fu, Yana, Zhao, Yun-e
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2023
Materias:
Clinical and Epidemiologic Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10615148/
https://www.ncbi.nlm.nih.gov/pubmed/37883092
http://dx.doi.org/10.1167/iovs.64.13.43

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10615148/
https://www.ncbi.nlm.nih.gov/pubmed/37883092
http://dx.doi.org/10.1167/iovs.64.13.43

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