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

Miles F. Greenwald; Ian D. Danford; Malika Shahrawat; Susan Ostmo; James Brown; Jayashree Kalpathy-Cramer; Kacy Bradshaw; Robert Schelonka; Howard S. Cohen; R. V.Paul Chan; Michael F. Chiang; J. Peter Campbell

doi:10.1016/j.jaapos.2020.01.014

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

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

Research output: Contribution to journal › Article › peer-review

34 Scopus citations

Abstract

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.

Original language	English (US)
Pages (from-to)	160-162
Number of pages	3
Journal	Journal of AAPOS
Volume	24
Issue number	3
DOIs	https://doi.org/10.1016/j.jaapos.2020.01.014
State	Published - Jun 2020

ASJC Scopus subject areas

Pediatrics, Perinatology, and Child Health
Ophthalmology

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10.1016/j.jaapos.2020.01.014

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title = "Evaluation of artificial intelligence-based telemedicine screening for retinopathy of prematurity",

abstract = "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.",

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AU - Greenwald, Miles F.

AU - Danford, Ian D.

AU - Shahrawat, Malika

AU - Ostmo, Susan

AU - Brown, James

AU - Kalpathy-Cramer, Jayashree

AU - Bradshaw, Kacy

AU - Schelonka, Robert

AU - Cohen, Howard S.

AU - Chan, R. V.Paul

AU - Chiang, Michael F.

AU - Campbell, J. Peter

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

Abstract

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