Photo by lukejonesdesign from unsplash
Key Points Question Can artificial intelligence estimate the visual function of eyes with retinitis pigmentosa from ultra-widefield fundus images? Findings In this multicenter cross-sectional study of 1274 eyes of 695… Click to show full abstract
Key Points Question Can artificial intelligence estimate the visual function of eyes with retinitis pigmentosa from ultra-widefield fundus images? Findings In this multicenter cross-sectional study of 1274 eyes of 695 patients with retinitis pigmentosa, the standardized regression coefficient was 0.309 in estimating visual acuity based on ultra-widefield fundus autofluorescence images using a deep learning model, 0.684 in estimating the mean deviation on the Humphrey field analyzer, and 0.697 in estimating central retinal sensitivity. Meaning Findings suggest that this estimation method of visual function using artificial intelligence with ultra-widefield fundus autofluorescence images assists in objectively evaluating the progression of retinitis pigmentosa.
Journal Title: JAMA Ophthalmology
Year Published: 2023
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!