An Outperforming Artificial Intelligence Model to Identify Referable Blepharoptosis for General Practitioners

The aim of this study is to develop an AI model that accurately identifies referable blepharoptosis automatically and to compare the AI model’s performance to a group of non-ophthalmic physicians. In total, 1000 retrospective single-eye images from tertiary oculoplastic clinics were labeled by three...

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Detalles Bibliográficos
Autores principales: Hung, Ju-Yi, Chen, Ke-Wei, Perera, Chandrashan, Chiu, Hsu-Kuang, Hsu, Cherng-Ru, Myung, David, Luo, An-Chun, Fuh, Chiou-Shann, Liao, Shu-Lang, Kossler, Andrea Lora
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877622/
https://www.ncbi.nlm.nih.gov/pubmed/35207771
http://dx.doi.org/10.3390/jpm12020283

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877622/
https://www.ncbi.nlm.nih.gov/pubmed/35207771
http://dx.doi.org/10.3390/jpm12020283

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