{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T18:37:02Z","timestamp":1791484622618,"version":"4.3.4"},"reference-count":56,"publisher":"Elsevier BV","issue":"4","license":[{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"funder":[{"DOI":"10.13039\/100000053","name":"National Eye Institute","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000053","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","theclinics.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pediatric Clinics of North America"],"published-print":{"date-parts":[[2020,8]]},"DOI":"10.1016\/j.pcl.2020.04.012","type":"journal-article","created":{"date-parts":[[2020,7,7]],"date-time":"2020-07-07T16:24:37Z","timestamp":1594139077000},"page":"725-733","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":36,"title":["Workforce Shortage for Retinopathy of Prematurity Care and Emerging Role of Telehealth and Artificial Intelligence"],"prefix":"10.1016","volume":"67","author":[{"given":"Alejandra","family":"Barrero-Castillero","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brian K.","family":"Corwin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deborah K.","family":"VanderVeen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jason C.","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.pcl.2020.04.012_bib1","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1542\/peds.2012-2996","article-title":"Screening examination of premature infants for retinopathy of prematurity","volume":"131","author":"Fierson","year":"2013","journal-title":"Pediatrics"},{"key":"10.1016\/j.pcl.2020.04.012_bib2","first-page":"493","article-title":"Long-term visual outcomes in extremely low-birth-weight children","volume":"104","author":"Spencer","year":"2006","journal-title":"Trans Am Ophthalmol Soc"},{"issue":"1","key":"10.1016\/j.pcl.2020.04.012_bib3","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1542\/peds.109.1.12","article-title":"Long-term ophthalmic outcome of low birth weight children with and without retinopathy of prematurity","volume":"109","author":"O\u2019Connor","year":"2002","journal-title":"Pediatrics"},{"key":"10.1016\/j.pcl.2020.04.012_bib5","doi-asserted-by":"crossref","first-page":"e003471","DOI":"10.1136\/bmjopen-2013-003471","article-title":"The economic burden of visual impairment and blindness: A systematic review","volume":"3","author":"K\u00f6berlein","year":"2013","journal-title":"BMJ Open"},{"issue":"2","key":"10.1016\/j.pcl.2020.04.012_bib6","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/j.clp.2017.01.009","article-title":"Survival of infants born at periviable gestational ages","volume":"44","author":"Patel","year":"2017","journal-title":"Clin Perinatol"},{"issue":"6","key":"10.1016\/j.pcl.2020.04.012_bib7","first-page":"541","article-title":"Predicting long-term visual outcome in children with birth weight under 1001 g","volume":"11","author":"O\u2019Connor","year":"2007","journal-title":"J\u00a0AAPOS"},{"issue":"7","key":"10.1016\/j.pcl.2020.04.012_bib8","doi-asserted-by":"crossref","first-page":"553","DOI":"10.3928\/23258160-20170630-06","article-title":"The epidemiology of retinopathy of prematurity in the united states","volume":"48","author":"Ludwig","year":"2017","journal-title":"Ophthalmic Surg Lasers Imaging Retina"},{"issue":"4","key":"10.1016\/j.pcl.2020.04.012_bib9","first-page":"344","article-title":"Retinopathy of prematurity care: patterns of care and workforce analysis","volume":"12","author":"Kemper","year":"2008","journal-title":"J\u00a0AAPOS"},{"key":"10.1016\/j.pcl.2020.04.012_bib10","article-title":"Survey: Physicians being driven away from ROP treatment","author":"Altersitz","year":"2006","journal-title":"Oculular Surgery News U.S. Edition"},{"issue":"6","key":"10.1016\/j.pcl.2020.04.012_bib11","doi-asserted-by":"crossref","first-page":"e20183061","DOI":"10.1542\/peds.2018-3061","article-title":"Screening examination of premature infants for retinopathy of prematurity","volume":"142","author":"Fierson","year":"2018","journal-title":"Pediatrics"},{"issue":"8","key":"10.1016\/j.pcl.2020.04.012_bib12","doi-asserted-by":"crossref","first-page":"992","DOI":"10.1001\/archophthalmol.2012.243","article-title":"Importance of early postnatal weight gain for normal retinal angiogenesis in very preterm infants: A multicenter study analyzing weight velocity deviations for the prediction of retinopathy of prematurity","volume":"130","author":"Wu","year":"2012","journal-title":"Arch Ophthalmol"},{"issue":"12","key":"10.1016\/j.pcl.2020.04.012_bib13","doi-asserted-by":"crossref","first-page":"1560","DOI":"10.1001\/archophthalmol.2012.2524","article-title":"The CHOP postnatal weight gain, birth weight, and gestational age retinopathy of prematurity risk model","volume":"130","author":"Binenbaum","year":"2012","journal-title":"Arch Ophthalmol"},{"issue":"3","key":"10.1016\/j.pcl.2020.04.012_bib14","doi-asserted-by":"crossref","first-page":"e607","DOI":"10.1542\/peds.2010-2240","article-title":"A\u00a0clinical prediction model to stratify retinopathy of prematurity risk using postnatal weight gain","volume":"127","author":"Binenbaum","year":"2011","journal-title":"Pediatrics"},{"issue":"4","key":"10.1016\/j.pcl.2020.04.012_bib15","doi-asserted-by":"crossref","first-page":"e638","DOI":"10.1542\/peds.2008-2697","article-title":"Early weight gain predicts retinopathy in preterm infants: New, simple, efficient approach to screening","volume":"123","author":"Hellstrom","year":"2009","journal-title":"Pediatrics"},{"issue":"11","key":"10.1016\/j.pcl.2020.04.012_bib16","doi-asserted-by":"crossref","first-page":"1433","DOI":"10.1001\/archophthalmol.2012.1890","article-title":"Improving preterm ophthalmologic care in\u00a0the era of accountable care organizations","volume":"130","author":"Wang","year":"2012","journal-title":"Arch Ophthalmol"},{"issue":"3","key":"10.1016\/j.pcl.2020.04.012_bib17","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1542\/peds.2007-0378","article-title":"Neonatologists\u2019 practices and experiences in arranging retinopathy of prematurity screening services","volume":"120","author":"Kemper","year":"2007","journal-title":"Pediatrics"},{"issue":"1","key":"10.1016\/j.pcl.2020.04.012_bib18","doi-asserted-by":"crossref","first-page":"e20161978","DOI":"10.1542\/peds.2016-1978","article-title":"Trends in the screening and treatment of retinopathy of prematurity","volume":"139","author":"Vartanian","year":"2017","journal-title":"Pediatrics"},{"issue":"7","key":"10.1016\/j.pcl.2020.04.012_bib19","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1001\/jamaophthalmol.2018.1934","article-title":"Automated diagnosis of plus disease in retinopathy of prematurity using deep convolutional neural networks","volume":"136","author":"Brown","year":"2018","journal-title":"JAMA Ophthalmol"},{"issue":"10","key":"10.1016\/j.pcl.2020.04.012_bib20","doi-asserted-by":"crossref","first-page":"1700","DOI":"10.1016\/S0161-6420(79)35329-5","article-title":"Fluorescein angiography in retrolental fibroplasia: Experience from 1969 - 1977","volume":"86","author":"Flynn","year":"1979","journal-title":"Ophthalmology"},{"issue":"236","key":"10.1016\/j.pcl.2020.04.012_bib21","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1136\/adc.44.236.499","article-title":"Retinal photography in the Newborn","volume":"44","author":"Bulpitt","year":"1969","journal-title":"Arch Dis Child"},{"issue":"6","key":"10.1016\/j.pcl.2020.04.012_bib22","first-page":"474","article-title":"Retinopathy of prematurity: Imaging in retinopathy of prematurity: where are we, and where are we going?","volume":"20","author":"Chiang","year":"2016","journal-title":"J\u00a0AAPOS"},{"issue":"2","key":"10.1016\/j.pcl.2020.04.012_bib23","first-page":"178","article-title":"Imaging in retinopathy of prematurity","volume":"8","author":"Valikodath","year":"2019","journal-title":"Asia Pac J Ophthalmol (Phila)"},{"issue":"2","key":"10.1016\/j.pcl.2020.04.012_bib24","first-page":"107","article-title":"RetCam imaging for retinopathy of prematurity screening","volume":"10","author":"Wu","year":"2006","journal-title":"J\u00a0AAPOS"},{"issue":"4","key":"10.1016\/j.pcl.2020.04.012_bib25","first-page":"352","article-title":"Agreement among pediatric ophthalmologists in diagnosing plus and pre-plus disease in retinopathy of prematurity","volume":"12","author":"Wallace","year":"2008","journal-title":"J\u00a0AAPOS"},{"issue":"3","key":"10.1016\/j.pcl.2020.04.012_bib26","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1001\/archopht.124.3.322","article-title":"Accuracy and reliability of remote retinopathy of prematurity diagnosis","volume":"124","author":"Chiang","year":"2006","journal-title":"Arch Ophthalmol"},{"issue":"7","key":"10.1016\/j.pcl.2020.04.012_bib27","doi-asserted-by":"crossref","first-page":"875","DOI":"10.1001\/archopht.125.7.875","article-title":"Interexpert agreement of plus disease diagnosis in retinopathy of prematurity","volume":"125","author":"Chiang","year":"2007","journal-title":"Arch Ophthalmol"},{"issue":"5\u20136","key":"10.1016\/j.pcl.2020.04.012_bib28","doi-asserted-by":"crossref","first-page":"214","DOI":"10.3109\/08820538.2010.523671","article-title":"Review of the use of digital imaging in retinopathy of prematurity screening","volume":"25","author":"Salcone","year":"2010","journal-title":"Semin Ophthalmol"},{"issue":"1","key":"10.1016\/j.pcl.2020.04.012_bib29","doi-asserted-by":"crossref","first-page":"e238","DOI":"10.1542\/peds.2014-0978","article-title":"Telemedicine for evaluation of retinopathy of prematurity","volume":"135","author":"Fierson","year":"2015","journal-title":"Pediatrics"},{"issue":"9","key":"10.1016\/j.pcl.2020.04.012_bib30","doi-asserted-by":"crossref","first-page":"1547","DOI":"10.1016\/j.ophtha.2006.03.056","article-title":"Impact of retinopathy of prematurity screening examination on cardiorespiratory indices. A comparison of indirect ophthalmoscopy and Retcam Imaging","volume":"113","author":"Mukherjee","year":"2006","journal-title":"Ophthalmology"},{"issue":"2","key":"10.1016\/j.pcl.2020.04.012_bib31","first-page":"64","article-title":"Telephotoscreening to detect retinopathy of prematurity: preliminary study of the optimum time to employ digital fundus camera imaging to detect ROP","volume":"6","author":"Yen","year":"2002","journal-title":"J\u00a0AAPOS"},{"issue":"10","key":"10.1016\/j.pcl.2020.04.012_bib32","doi-asserted-by":"crossref","first-page":"1292","DOI":"10.1136\/bjo.2006.091900","article-title":"Remote image based retinopathy of prematurity diagnosis: A receiver operating characteristic analysis of accuracy","volume":"90","author":"Chiang","year":"2006","journal-title":"Br J Ophthalmol"},{"issue":"6","key":"10.1016\/j.pcl.2020.04.012_bib33","doi-asserted-by":"crossref","first-page":"1272","DOI":"10.1016\/j.ophtha.2012.01.002","article-title":"Detection of clinically significant retinopathy of prematurity using wide-angle digital retinal photography: A report by the American Academy of Ophthalmology","volume":"119","author":"Chiang","year":"2012","journal-title":"Ophthalmology"},{"issue":"1","key":"10.1016\/j.pcl.2020.04.012_bib34","article-title":"Diagnostic accuracy of ophthalmoscopy vs telemedicine in examinations for retinopathy of prematurity","volume":"136","author":"Biten","year":"2018","journal-title":"JAMA Ophthalmol"},{"issue":"2","key":"10.1016\/j.pcl.2020.04.012_bib35","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.jcjo.2014.11.005","article-title":"SUNDROP: Six years of screening for retinopathy of prematurity with telemedicine","volume":"50","author":"Wang","year":"2015","journal-title":"Can J Ophthalmol"},{"issue":"9","key":"10.1016\/j.pcl.2020.04.012_bib36","doi-asserted-by":"crossref","first-page":"1251","DOI":"10.1007\/s00417-009-1077-7","article-title":"Wide-field digital imaging based telemedicine for screening for acute retinopathy of prematurity (ROP). Six-year results of a multicentre field study","volume":"247","author":"Lorenz","year":"2009","journal-title":"Graefes Arch Clin Exp Ophthalmol"},{"issue":"5","key":"10.1016\/j.pcl.2020.04.012_bib37","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/j.siny.2015.05.002","article-title":"Role of tele-medicine in retinopathy of prematurity screening in rural outreach centers in India - a report of 20,214 imaging sessions in the KIDROP program","volume":"20","author":"Vinekar","year":"2015","journal-title":"Semin Fetal Neonatal Med"},{"issue":"13","key":"10.1016\/j.pcl.2020.04.012_bib38","doi-asserted-by":"crossref","first-page":"1317","DOI":"10.1001\/jama.2017.18391","article-title":"Big data and machine learning in health care","volume":"319","author":"Beam","year":"2018","journal-title":"JAMA"},{"issue":"11","key":"10.1016\/j.pcl.2020.04.012_bib39","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.1001\/jama.2018.11100","article-title":"Deep learning\u2014a technology with the potential to transform health care","volume":"320","author":"Hinton","year":"2018","journal-title":"JAMA"},{"issue":"22","key":"10.1016\/j.pcl.2020.04.012_bib40","doi-asserted-by":"crossref","first-page":"2368","DOI":"10.1001\/jama.2016.17217","article-title":"Translating artificial intelligence into clinical care","volume":"316","author":"Beam","year":"2016","journal-title":"JAMA"},{"issue":"10","key":"10.1016\/j.pcl.2020.04.012_bib41","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1038\/s41551-018-0305-z","article-title":"Artificial intelligence in healthcare","volume":"2","author":"Yu","year":"2018","journal-title":"Nat Biomed Eng"},{"issue":"4","key":"10.1016\/j.pcl.2020.04.012_bib42","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1136\/svn-2017-000101","article-title":"Artificial intelligence in healthcare: Past, present and future","volume":"2","author":"Jiang","year":"2017","journal-title":"Stroke Vasc Neurol"},{"issue":"22","key":"10.1016\/j.pcl.2020.04.012_bib43","doi-asserted-by":"crossref","first-page":"2402","DOI":"10.1001\/jama.2016.17216","article-title":"Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs","volume":"316","author":"Gulshan","year":"2016","journal-title":"JAMA"},{"key":"10.1016\/j.pcl.2020.04.012_bib44","doi-asserted-by":"crossref","DOI":"10.1001\/jamaophthalmol.2019.2004","article-title":"Performance of a deep-learning algorithm vs manual grading for detecting diabetic retinopathy in indiaperformance of a deep-learning algorithm vs manual grading for detecting diabetic retinopathy in indiaperformance of a deep-learning algorithm vs manual","author":"Gulshan","year":"2019","journal-title":"JAMA Ophthalmol"},{"key":"10.1016\/j.pcl.2020.04.012_bib45","series-title":"A\u00a0comprehensive guide to convolutional neural networks \u2014 the ELI5 way. Towards data science","author":"Saha","year":"2018"},{"issue":"2014","key":"10.1016\/j.pcl.2020.04.012_bib46","first-page":"1902","article-title":"Development and evaluation of reference standards for image-based telemedicine diagnosis and clinical research studies in ophthalmology","volume":"14","author":"Ryan","year":"2014","journal-title":"AMIA Annu Symp Proc"},{"issue":"5","key":"10.1016\/j.pcl.2020.04.012_bib47","doi-asserted-by":"crossref","first-page":"444","DOI":"10.1016\/j.oret.2019.01.015","article-title":"Automated fundus image quality assessment in retinopathy of prematurity using deep convolutional neural networks","volume":"3","author":"Coyner","year":"2019","journal-title":"Ophthalmol Retina"},{"key":"10.1016\/j.pcl.2020.04.012_bib48","doi-asserted-by":"crossref","DOI":"10.1001\/jamaophthalmol.2019.2433","article-title":"Monitoring disease progression with a quantitative severity scale for retinopathy of prematurity using deep learning","author":"Taylor","year":"2019","journal-title":"JAMA Ophthalmol"},{"key":"10.1016\/j.pcl.2020.04.012_bib49","doi-asserted-by":"crossref","DOI":"10.1001\/jamaophthalmol.2019.2442","article-title":"A\u00a0quantitative severity scale for retinopathy of prematurity using deep learning to monitor disease regression after treatment","author":"Gupta","year":"2019","journal-title":"JAMA Ophthalmol"},{"issue":"7639","key":"10.1016\/j.pcl.2020.04.012_bib50","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1038\/nature21056","article-title":"Dermatologist-level classification of skin cancer with deep neural networks","volume":"542","author":"Esteva","year":"2017","journal-title":"Nature"},{"issue":"1","key":"10.1016\/j.pcl.2020.04.012_bib51","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1148\/radiol.2017170236","article-title":"Performance of a deep-learning neural network model in assessing skeletal maturity on pediatric hand radiographs","volume":"287","author":"Larson","year":"2018","journal-title":"Radiology"},{"issue":"22","key":"10.1016\/j.pcl.2020.04.012_bib52","doi-asserted-by":"crossref","first-page":"2199","DOI":"10.1001\/jama.2017.14585","article-title":"Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer","volume":"318","author":"Bejnordi","year":"2017","journal-title":"JAMA"},{"key":"10.1016\/j.pcl.2020.04.012_bib53","series-title":"FDA permits marketing of artificial intelligence-based device to detect certain diabetes-related eye problems. FDA News Release","year":"2018"},{"key":"10.1016\/j.pcl.2020.04.012_bib54","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1038\/s41746-018-0040-6","article-title":"Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices","volume":"1","author":"Abr\u00e0moff","year":"2018","journal-title":"NPJ Digit Med"},{"issue":"3","key":"10.1016\/j.pcl.2020.04.012_bib55","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1038\/s41551-018-0195-0","article-title":"Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning","volume":"2","author":"Poplin","year":"2018","journal-title":"Nat Biomed Eng"},{"issue":"3","key":"10.1016\/j.pcl.2020.04.012_bib56","first-page":"158","article-title":"Top five legal pitfalls in retinopathy of prematurity","volume":"2","author":"Moshfeghi","year":"2018","journal-title":"Curr Opin Ophthalmol"},{"issue":"1\u20132","key":"10.1016\/j.pcl.2020.04.012_bib57","doi-asserted-by":"crossref","first-page":"159","DOI":"10.3109\/08820538.2015.1114859","article-title":"Computer-assisted digital image analysis of plus disease in retinopathy of prematurity","volume":"31","author":"Kemp","year":"2016","journal-title":"Semin Ophthalmol"}],"container-title":["Pediatric Clinics of North America"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031395520300419?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031395520300419?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,21]],"date-time":"2025-09-21T17:24:17Z","timestamp":1758475457000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031395520300419"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8]]},"references-count":56,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2020,8]]}},"alternative-id":["S0031395520300419"],"URL":"https:\/\/doi.org\/10.1016\/j.pcl.2020.04.012","relation":{},"ISSN":["0031-3955"],"issn-type":[{"value":"0031-3955","type":"print"}],"subject":[],"published":{"date-parts":[[2020,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Workforce Shortage for Retinopathy of Prematurity Care and Emerging Role of Telehealth and Artificial Intelligence","name":"articletitle","label":"Article Title"},{"value":"Pediatric Clinics of North America","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.pcl.2020.04.012","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2020 Elsevier Inc. All rights reserved.","name":"copyright","label":"Copyright"}]}}