A Multihead Attention Deep Learning Algorithm to Detect Amblyopia Using Fixation Eye Movements

To develop an attention-based deep learning (DL) model based on eye movements acquired during a simple visual fixation task to detect amblyopic subjects across different types and severity from controls. An observational study. We recruited 40 controls and 95 amblyopic subjects (anisometropic = 32;...

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Bibliographic Details
Published in:	Ophthalmology science (Online) Vol. 5; no. 5; p. 100775
Main Authors:	Upadhyaya, Dipak P., Cakir, Gokce, Ramat, Stefano, Albert, Jeffrey, Shaikh, Aasef, Sahoo, Satya S., Ghasia, Fatema
Format:	Journal Article
Language:	English
Published:	Netherlands Elsevier Inc 01.09.2025 Elsevier
Subjects:	Amblyopia Artificial intelligence Eye tracking Fixation eye movements Ophthalmology Original Strabismus Strabismus D FMN DL MV Fixation eye movements FEM AEV BV AUPRC FEV Amblyopia Artificial intelligence Eye tracking fixation eye movement amblyopic eye viewing binocular viewing fusion maldevelopment nystagmus deep learning area under the precision–recall curve diopters fellow eye viewing monocular viewin
ISSN:	2666-9145, 2666-9145
Online Access:	Get full text
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