2022
Detecting visually significant cataract using retinal photograph-based deep learning
Tham Y, Goh J, Anees A, Lei X, Rim T, Chee M, Wang Y, Jonas J, Thakur S, Teo Z, Cheung N, Hamzah H, Tan G, Husain R, Sabanayagam C, Wang J, Chen Q, Lu Z, Keenan T, Chew E, Tan A, Mitchell P, Goh R, Xu X, Liu Y, Wong T, Cheng C. Detecting visually significant cataract using retinal photograph-based deep learning. Nature Aging 2022, 2: 264-271. PMID: 37118370, PMCID: PMC10154193, DOI: 10.1038/s43587-022-00171-6.Peer-Reviewed Original Research
2021
Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen: Toward automated and accessible classification of age-related macular degeneration
Chen Q, Keenan T, Allot A, Peng Y, Agrón E, Domalpally A, Klaver C, Luttikhuizen D, Colyer M, Cukras C, Wiley H, Magone M, Cousineau-Krieger C, Wong W, Zhu Y, Chew E, Lu Z, Group F. Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen: Toward automated and accessible classification of age-related macular degeneration. Journal Of The American Medical Informatics Association 2021, 28: 1135-1148. PMID: 33792724, PMCID: PMC8200273, DOI: 10.1093/jamia/ocaa302.Peer-Reviewed Original ResearchConceptsColor fundus photographyAge-related macular degenerationFundus autofluorescenceReticular pseudodrusenMacular degenerationStandard color fundus photographyReceiver-operating characteristic curveAdvanced imaging modalitiesExternal validationRetinal specialistsAMD featuresFundus photographyGeographic atrophyPigmentary abnormalitiesAMD diagnosisImaging modalitiesCharacteristic curvePseudodrusenDegeneration