Predicting Visual Improvement After Macular Hole Surgery: A Combined Model Using Deep Learning and Clinical Features | Zendy

Alexandre Lachance | Zendy; Mathieu Godbout | Zendy; Fares Antaki | Zendy; Mélanie Hébert | Zendy; Serge Bourgault | Zendy; Mathieu Caissie | Zendy; Éric Tourville | Zendy; Audrey Durand | Zendy; Ali Dirani | Zendy

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Predicting Visual Improvement After Macular Hole Surgery: A Combined Model Using Deep Learning and Clinical Features

Author(s) -

Alexandre Lachance,

Mathieu Godbout,

Fares Antaki,

Mélanie Hébert,

Serge Bourgault,

Mathieu Caissie,

Éric Tourville,

Audrey Durand,

Ali Dirani

Publication year - 2022

Publication title -

translational vision science and technology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.508

H-Index - 21

ISSN - 2164-2591

DOI - 10.1167/tvst.11.4.6

Subject(s) - optical coherence tomography , receiver operating characteristic , artificial intelligence , convolutional neural network , logistic regression , medicine , diabetic retinopathy , deep learning , regression , visual acuity , feature (linguistics) , ophthalmology , pattern recognition (psychology) , computer science , mathematics , statistics , diabetes mellitus , linguistics , philosophy , endocrinology

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