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For: Scruggs BA, Chan RVP, Kalpathy-Cramer J, Chiang MF, Campbell JP. Artificial Intelligence in Retinopathy of Prematurity Diagnosis. Transl Vis Sci Technol 2020;9:5. [PMID: 32704411 DOI: 10.1167/tvst.9.2.5] [Cited by in Crossref: 12] [Cited by in F6Publishing: 8] [Article Influence: 6.0] [Reference Citation Analysis]
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5 Ramachandran S, Niyas P, Vinekar A, John R. A deep learning framework for the detection of Plus disease in retinal fundus images of preterm infants. Biocybernetics and Biomedical Engineering 2021;41:362-75. [DOI: 10.1016/j.bbe.2021.02.005] [Cited by in Crossref: 3] [Article Influence: 3.0] [Reference Citation Analysis]
6 Gensure RH, Chiang MF, Campbell JP. Artificial intelligence for retinopathy of prematurity. Curr Opin Ophthalmol 2020;31:312-7. [PMID: 32694266 DOI: 10.1097/ICU.0000000000000680] [Cited by in Crossref: 7] [Article Influence: 3.5] [Reference Citation Analysis]
7 Ademola-Popoola DS, Fajolu IB, Gilbert C, Olusanya BA, Onakpoya OH, Ezisi CN, Musa KO, Chan RVP, Okeigbemen VW, Muhammad RC, Malik ANJ, Adio AO, Bodunde OT, Rafindadi AL, Oluleye TS, Tongo OO, Badmus SA, Adebara OV, Padhi TR, Ezenwa BN, Obajolowo TS, Olokoba LB, Olatunji VA, Babalola YO, Ugalahi MO, Adenekan A, Adesiyun OO, Sahoo J, Miller MT, Uhumwangho OM, Olagbenro AS, Adejuyigbe EA, Ezeaka CVC, Mokuolu O, Ogunlesi TA, Ogunfowora OB, Abdulkadir I, Abdullahi FL, Fabiyi AT, Hassan LHL, Baiyeroju AM, Opara PI, Oladigbolu K, Eneh AU, Fiebai BE, Mahmud-Ajeigbe FA, Peter EN, Abdullahi HS. Strengthening retinopathy of prematurity screening and treatment services in Nigeria: a case study of activities, challenges and outcomes 2017-2020. BMJ Open Ophthalmol 2021;6:e000645. [PMID: 34514173 DOI: 10.1136/bmjophth-2020-000645] [Reference Citation Analysis]
8 Campbell JP, Chiang MF, Chen JS, Moshfeghi DM, Nudleman E, Ruambivoonsuk P, Cherwek H, Cheung CY, Singh P, Kalpathy-cramer J, Ostmo S, Eydelman M, Chan RP, Capone A. Artificial Intelligence for Retinopathy of Prematurity: Validation of a Vascular Severity Scale against International Expert Diagnosis. Ophthalmology 2022. [DOI: 10.1016/j.ophtha.2022.02.008] [Reference Citation Analysis]
9 Antaki F, Bachour K, Kim TN, Qian CX. The Role of Telemedicine to Alleviate an Increasingly Burdened Healthcare System: Retinopathy of Prematurity. Ophthalmol Ther 2020;9:449-64. [PMID: 32562242 DOI: 10.1007/s40123-020-00275-5] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
10 Azad R, Gilbert C, Gangwe AB, Zhao P, Wu W, Sarbajna P, Vinekar A. Retinopathy of Prematurity: How to Prevent the Third Epidemics in Developing Countries. Asia-Pacific Journal of Ophthalmology 2020;9:440-8. [DOI: 10.1097/apo.0000000000000313] [Cited by in Crossref: 2] [Article Influence: 1.0] [Reference Citation Analysis]
11 Nikolaidou A, Tsaousis KT. Teleophthalmology and Artificial Intelligence As Game Changers in Ophthalmic Care After the COVID-19 Pandemic. Cureus 2021;13:e16392. [PMID: 34408945 DOI: 10.7759/cureus.16392] [Reference Citation Analysis]
12 Chen JS, Coyner AS, Ostmo S, Sonmez K, Bajimaya S, Pradhan E, Valikodath N, Cole ED, Al-Khaled T, Chan RVP, Singh P, Kalpathy-Cramer J, Chiang MF, Campbell JP. Deep Learning for the Diagnosis of Stage in Retinopathy of Prematurity: Accuracy and Generalizability across Populations and Cameras. Ophthalmol Retina 2021;5:1027-35. [PMID: 33561545 DOI: 10.1016/j.oret.2020.12.013] [Reference Citation Analysis]
13 Caruso M, Ricciardi C, Delli Paoli G, Di Dato F, Donisi L, Romeo V, Petretta M, Iorio R, Cesarelli G, Brunetti A, Maurea S. Machine Learning Evaluation of Biliary Atresia Patients to Predict Long-Term Outcome after the Kasai Procedure. Bioengineering (Basel) 2021;8:152. [PMID: 34821718 DOI: 10.3390/bioengineering8110152] [Reference Citation Analysis]
14 Agarwal K, Vinekar A, Chandra P, Padhi TR, Nayak S, Jayanna S, Panchal B, Jalali S, Das T. Imaging the pediatric retina: An overview. Indian J Ophthalmol 2021;69:812-23. [PMID: 33727440 DOI: 10.4103/ijo.IJO_1917_20] [Reference Citation Analysis]