AI Medical Compendium Journal:
JAMA ophthalmology

Showing 41 to 50 of 60 articles

Model-to-Data Approach for Deep Learning in Optical Coherence Tomography Intraretinal Fluid Segmentation.

JAMA ophthalmology
IMPORTANCE: Amid an explosion of interest in deep learning in medicine, including within ophthalmology, concerns regarding data privacy, security, and sharing are of increasing importance. A model-to-data approach, in which the model itself is transf...

Screening Candidates for Refractive Surgery With Corneal Tomographic-Based Deep Learning.

JAMA ophthalmology
IMPORTANCE: Evaluating corneal morphologic characteristics with corneal tomographic scans before refractive surgery is necessary to exclude patients with at-risk corneas and keratoconus. In previous studies, researchers performed screening with machi...

Characterization of Central Visual Field Loss in End-stage Glaucoma by Unsupervised Artificial Intelligence.

JAMA ophthalmology
IMPORTANCE: Although the central visual field (VF) in end-stage glaucoma may substantially vary among patients, structure-function studies and quality-of-life assessments are impeded by the lack of appropriate characterization of end-stage VF loss.