Machine learning-based prediction of anatomical outcome after idiopathic macular hole surgery

BACKGROUND: To develop a machine learning (ML) model for the prediction of the idiopathic macular hole (IMH) status at 1 month after vitrectomy and internal limiting membrane peeling (VILMP) surgery. METHODS: A total of 288 IMH eyes from four ophthalmic centers were enrolled. All eyes underwent opti...

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Detalles Bibliográficos
Autores principales: Xiao, Yu, Hu, Yijun, Quan, Wuxiu, Zhang, Bin, Wu, Yuqing, Wu, Qiaowei, Liu, Baoyi, Zeng, Xiaomin, Lin, Zhanjie, Fang, Ying, Hu, Yu, Feng, Songfu, Yuan, Ling, Cai, Hongmin, Yu, Honghua, Li, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184483/
https://www.ncbi.nlm.nih.gov/pubmed/34164464
http://dx.doi.org/10.21037/atm-20-8065

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8184483/
https://www.ncbi.nlm.nih.gov/pubmed/34164464
http://dx.doi.org/10.21037/atm-20-8065

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