An artificial intelligence model for the simulation of visual effects in patients with visual field defects

BACKGROUND: This study aimed to simulate the visual field (VF) effects of patients with VF defects using deep learning and computer vision technology. METHODS: We collected 3,660 Humphrey visual fields (HVFs) as data samples, including 3,263 reliable 24-2 HVFs. The convolutional neural network (CNN)...

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Detalles Bibliográficos
Autores principales: Zhou, Zhan, Li, Bingbing, Su, Jinyu, Fan, Xianming, Chen, Liang, Tang, Song, Zheng, Jianqing, Zhang, Tong, Meng, Zhiyong, Chen, Zhimeng, Deng, Hongwei, Hu, Jianmin, Zhao, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Original Article on Medical Artificial Intelligent Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327351/
https://www.ncbi.nlm.nih.gov/pubmed/32617323
http://dx.doi.org/10.21037/atm.2020.02.162

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327351/
https://www.ncbi.nlm.nih.gov/pubmed/32617323
http://dx.doi.org/10.21037/atm.2020.02.162

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