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 photographsPredicting myocardial infarction through retinal scans and minimal personal information
Diaz-Pinto A, Ravikumar N, Attar R, Suinesiaputra A, Zhao Y, Levelt E, Dall’Armellina E, Lorenzi M, Chen Q, Keenan T, Agrón E, Chew E, Lu Z, Gale C, Gale R, Plein S, Frangi A. Predicting myocardial infarction through retinal scans and minimal personal information. Nature Machine Intelligence 2022, 4: 55-61. DOI: 10.1038/s42256-021-00427-7.Peer-Reviewed Original ResearchVentricular end-diastolic volumeLeft ventricular massEnd-diastolic volumeMyocardial infarctionVentricular massPrimary eye diseaseFuture myocardial infarctionIncident myocardial infarctionCoronary artery diseaseBlood vessel densityRetinal imagesArtery diseaseEye clinicCardiac functionDiabetic retinopathySystemic conditionsEye diseaseHigh riskVessel densityInfarctionRetinal imagingDemographic dataOphthalmologic practicePatientsDisease
2020
Predicting risk of late age-related macular degeneration using deep learning
Peng Y, Keenan T, Chen Q, Agrón E, Allot A, Wong W, Chew E, Lu Z. Predicting risk of late age-related macular degeneration using deep learning. Npj Digital Medicine 2020, 3: 111. PMID: 32904246, PMCID: PMC7453007, DOI: 10.1038/s41746-020-00317-z.Peer-Reviewed Original ResearchLate age-related macular degenerationAge-related macular degenerationHigher prognostic accuracyClinical standardsMacular degenerationPrognostic accuracyIndependent cohortLargest longitudinal clinical trialsProbability of progressionSight-threatening stagesColor fundus photographsLongitudinal clinical trialsAMD patientsRetinal specialistsClinical trialsFundus photographsSpecialty clinicHigh riskClinical actionsSurvival analysisMedical interventionsIndividual riskAREDS2AREDSExternal validation