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Ophthalmology
Meta-analysis
AI models detect retinal detachment with 95.7% sensitivity and 99.2% specificity in meta-analysis
Machine learning models show high accuracy in detecting retinal detachment
This meta-analysis of 69 models evaluated machine learning and deep learning for retinal detachment detection, reporting pooled sensitivity …
New data shows that deep learning models can identify retinal detachment with over 96% sensitivity, helping doctors catch eye issues faster.
Sep 4, 2026
Ophthalmology
Meta-analysis
Network meta-analysis compares adjunctive therapies for proliferative vitreoretinopathy
Oral retinoic acid shows promise for retinal detachment repair
Oral retinoic acid significantly improves retinal reattachment rates in PVR patients, with strong evidence for visual acuity and reduced com…
A study found oral retinoic acid may improve retinal reattachment rates after surgery for certain eye conditions, offering a potential new t…
Jun 1, 2026
Ophthalmology
Meta-analysis
Vitreoretinal surgery yields high reattachment rates in familial exudative vitreoretinopathy-associated retinal detachment
Surgery outcomes for FEVR retinal detachment vary by procedure type and disease stage
This systematic review and meta-analysis evaluated 682 eyes from 19 observational studies of patients with familial exudative…
Surgery success for FEVR retinal detachment depends on disease stage, with scleral buckling achieving a 90 percent reattachment rate for sim…
Apr 6, 2026