Portal de Periódicos da CAPES

Evaluation of artificial intelligence-based telemedicine screening for retinopathy of prematurity

2020; Elsevier BV; Volume: 24; Issue: 3 Linguagem: Inglês

10.1016/j.jaapos.2020.01.014

1528-3933

Miles F. Greenwald, Ian Danford, Malika Shahrawat, Susan Ostmo, James M. Brown, Jayashree Kalpathy‐Cramer, Kacy Bradshaw, Robert L. Schelonka, Howard Cohen, R.V. Paul Chan, Michael F. Chiang, J. Peter Campbell,

Retinal Diseases and Treatments

Retrospective evaluation of a deep learning–derived retinopathy of prematurity (ROP) vascular severity score in an operational ROP screening program demonstrated high diagnostic performance for detection of type 2 or worse ROP. To our knowledge, this is the first report in the literature that evaluated the use of artificial intelligence for ROP screening and represents a proof of concept. With further prospective validation, this technology might improve the accuracy, efficiency, and objectivity of diagnosis and facilitate earlier detection of disease progression in patients with potentially blinding ROP. Retrospective evaluation of a deep learning–derived retinopathy of prematurity (ROP) vascular severity score in an operational ROP screening program demonstrated high diagnostic performance for detection of type 2 or worse ROP. To our knowledge, this is the first report in the literature that evaluated the use of artificial intelligence for ROP screening and represents a proof of concept. With further prospective validation, this technology might improve the accuracy, efficiency, and objectivity of diagnosis and facilitate earlier detection of disease progression in patients with potentially blinding ROP.