This paper is in the following e-collection/theme issue:

Reviews in Medical Informatics (93) Machine Learning (1465) Decision Support for Health Professionals (1185) Electronic Health Records (1053) Ophthalmology (44) Tools, Programs and Algorithms (266) Computer-Aided Diagnosis (128)

Published on in Vol 9, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27363, first published .
Machine Learning Algorithms to Detect Subclinical Keratoconus: Systematic Review

Machine Learning Algorithms to Detect Subclinical Keratoconus: Systematic Review

Machine Learning Algorithms to Detect Subclinical Keratoconus: Systematic Review

Authors of this article:

Howard Maile1 Author Orcid Image ;   Ji-Peng Olivia Li2 Author Orcid Image ;   Daniel Gore2 Author Orcid Image ;   Marcello Leucci2 Author Orcid Image ;   Padraig Mulholland1, 2, 3 Author Orcid Image ;   Scott Hau2 Author Orcid Image ;   Anita Szabo1 Author Orcid Image ;   Ismail Moghul2 Author Orcid Image ;   Konstantinos Balaskas2 Author Orcid Image ;   Kaoru Fujinami1, 2, 4, 5 Author Orcid Image ;   Pirro Hysi6, 7 Author Orcid Image ;   Alice Davidson1 Author Orcid Image ;   Petra Liskova8, 9 Author Orcid Image ;   Alison Hardcastle1 Author Orcid Image ;   Stephen Tuft1, 2 Author Orcid Image ;   Nikolas Pontikos1, 2 Author Orcid Image
Article Authors Cited by (14) Tweetations (24) Metrics

Journals

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  12. Fujinami-Yokokawa Y, Joo K, Liu X, Tsunoda K, Kondo M, Ahn S, Robson A, Naka I, Ohashi J, Li H, Yang L, Arno G, Pontikos N, Park K, Michaelides M, Tachimori H, Miyata H, Sui R, Woo S, Fujinami K. Distinct Clinical Effects of Two RP1L1 Hotspots in East Asian Patients With Occult Macular Dystrophy (Miyake Disease): EAOMD Report 4. Investigative Opthalmology & Visual Science 2024;65(1):41 View
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