A Multitask Deep-Learning System to Classify Diabetic Macular Edema for Different Optical Coherence Tomography Devices: A Multicenter Analysis.

Fangyao TangXi WangAn-Ran RanCarmen K M ChanMary HoWilson YipAlvin L YoungJerry LokSimon SzetoJason ChanFanny YipRaymond WongZiqi TangDawei YangDanny S NgLi Jia ChenMarten BrelénVictor ChuKenneth LiTracy H T LaiGavin S TanDaniel S W TingHaifan HuangHaoyu ChenJacey Hongjie MaShibo TangTheodore LengSchahrouz KakavandSuria S MannilRobert T ChangGerald LiewBamini GopinathTimothy Y Y LaiChi Pui PangPeter H ScanlonTien Yin WongClement C ThamHao ChenPheng-Ann HengCarol Yim-Lui Cheung

Published in: Diabetes care (2021)

We demonstrated excellent performance with a DL system for the automated classification of DME, highlighting its potential as a promising second-line screening tool for patients with DM, which may potentially create a more effective triaging mechanism to eye clinics.

Keyphrases

deep learning
machine learning
optical coherence tomography
artificial intelligence
convolutional neural network
primary care
double blind
weight loss
glycemic control