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ABSTRACT: Purpose
To use supervised machine learning to predict visual function from retinal structure in retinitis pigmentosa (RP) and apply these estimates to CEP290- and NPHP5-associated Leber congenital amaurosis (LCA) to determine the potential for functional improvement.Methods
Patients with RP (n = 20) and LCA due to CEP290 (n = 12) or NPHP5 (n = 6) mutations were studied. A patient with CEP290 mutations but mild retinal degeneration was included. RP patients had cone-mediated macular function. A machine learning technique was used to associate perimetric sensitivities to local structure in RP patients. Models trained on RP data were applied to predict visual function in LCA.Results
The RP and LCA patients had comparable retinal structure. RP patients had peak sensitiv
SUBMITTER: Sumaroka A
PROVIDER: S-EPMC6586080 | biostudies-literature | 2019 Jun
REPOSITORIES: biostudies-literature