2022
Reticular Pseudodrusen: The Third Macular Risk Feature for Progression to Late Age-Related Macular Degeneration Age-Related Eye Disease Study 2 Report 30
Agrón E, Domalpally A, Cukras C, Clemons T, Chen Q, Lu Z, Chew E, Keenan T, Groups A. Reticular Pseudodrusen: The Third Macular Risk Feature for Progression to Late Age-Related Macular Degeneration Age-Related Eye Disease Study 2 Report 30. Ophthalmology 2022, 129: 1107-1119. PMID: 35660417, PMCID: PMC9509418, DOI: 10.1016/j.ophtha.2022.05.021.Peer-Reviewed Original ResearchConceptsLate age-related macular degenerationAge-related macular degenerationAge-related eye disease studyNeovascular age-related macular degenerationColor fundus photographsHazard ratioReticular pseudodrusenGeographic atrophyHigh riskRisk factorsSeverity ScalePresence of RPDProportional hazards regression analysisMacular Degeneration AgeClinical trial cohortIndependent risk factorEye Disease StudyHazards regression analysisImportant risk factorFundus autofluorescence imagesAMD severity scaleTrial cohortRisk calculatorClinical trialsFundus photographs
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
2019
A Deep Learning Approach for Automated Detection of Geographic Atrophy from Color Fundus Photographs
Keenan T, Dharssi S, Peng Y, Chen Q, Agrón E, Wong W, Lu Z, Chew E. A Deep Learning Approach for Automated Detection of Geographic Atrophy from Color Fundus Photographs. Ophthalmology 2019, 126: 1533-1540. PMID: 31358385, PMCID: PMC6810830, DOI: 10.1016/j.ophtha.2019.06.005.Peer-Reviewed Original Research