2024
Deep-RPD-Net: A 3D Deep Network for Detection of Reticular Pseudodrusen on Optical Coherence Tomography Scans
Elsawy A, Keenan T, Thavikulwat A, Lu A, Bellur S, Mukherjee S, Agron E, Chen Q, Chew E, Lu Z. Deep-RPD-Net: A 3D Deep Network for Detection of Reticular Pseudodrusen on Optical Coherence Tomography Scans. Ophthalmology Science 2024, 100655. DOI: 10.1016/j.xops.2024.100655.Peer-Reviewed Original ResearchSemi-supervised learningReticular pseudodrusenOCT scansRetina specialistsOptical coherence tomographyArea under ROC curveSpectral-domain optical coherence tomographyBaseline modelOptical coherence tomography scansAge-Related Macular Degeneration StudyDetect reticular pseudodrusenFundus autofluorescence imagingDeep learning networkDeep networksBaseline methodsPretrained modelsModel decision-makingReading centerLearning networkHigh-performance metricsOCT studiesTomography scanAREDS2En faceCoherence tomographyAn Updated Simplified Severity Scale for Age-Related Macular Degeneration Incorporating Reticular Pseudodrusen Age-Related Eye Disease Study Report Number 42
Agrón E, Domalpally A, Chen Q, Lu Z, Chew E, Keenan T, Groups A. An Updated Simplified Severity Scale for Age-Related Macular Degeneration Incorporating Reticular Pseudodrusen Age-Related Eye Disease Study Report Number 42. Ophthalmology 2024, 131: 1164-1174. PMID: 38657840, PMCID: PMC11416341, DOI: 10.1016/j.ophtha.2024.04.011.Peer-Reviewed Original ResearchAge-Related Eye Disease StudyProgression to late AMDReticular pseudodrusenLate AMDFive-year ratesProgression rateAge-related macular degenerationSeverity ScaleEye Disease StudyClinical trial cohortIncrease prognostic accuracyPost hoc analysisMacular degenerationAREDS2Prognostic accuracyTrial cohortRisk featuresHoc analysisRisk categorizationPseudodrusenAge-relatedBaselineDisease StudyRiskExternal validation
2023
A deep network DeepOpacityNet for detection of cataracts from color fundus photographs
Elsawy A, Keenan T, Chen Q, Thavikulwat A, Bhandari S, Quek T, Goh J, Tham Y, Cheng C, Chew E, Lu Z. A deep network DeepOpacityNet for detection of cataracts from color fundus photographs. Communications Medicine 2023, 3: 184. PMID: 38104223, PMCID: PMC10725427, DOI: 10.1038/s43856-023-00410-w.Peer-Reviewed Original ResearchColor fundus photographyAnterior segment photographsSlit-lamp examinationEye Disease StudyPosterior subcapsular cataractColor fundus photographsAREDS2 participantsCataract presenceSingapore EpidemiologyDetection of cataractOphthalmology clinicFundus photographyFundus photographsSubcapsular cataractCenter gradingCataractOphthalmologistsDisease StudyBlood vesselsNuclear cataractPerson evaluationAREDS2ClinicEpidemiologyDiagnosis
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