2024
Uncertainty-aware deep-learning model for prediction of supratentorial hematoma expansion from admission non-contrast head computed tomography scan
Tran A, Zeevi T, Haider S, Abou Karam G, Berson E, Tharmaseelan H, Qureshi A, Sanelli P, Werring D, Malhotra A, Petersen N, de Havenon A, Falcone G, Sheth K, Payabvash S. Uncertainty-aware deep-learning model for prediction of supratentorial hematoma expansion from admission non-contrast head computed tomography scan. Npj Digital Medicine 2024, 7: 26. PMID: 38321131, PMCID: PMC10847454, DOI: 10.1038/s41746-024-01007-w.Peer-Reviewed Original ResearchDeep learning modelsHematoma expansionIntracerebral hemorrhageICH expansionComputed tomographyNon-contrast head CTNon-contrast head computed tomographyHigh risk of HEHead Computed TomographyHigh-confidence predictionsRisk of HENon-contrast headReceiver operating characteristic areaModifiable risk factorsMonte Carlo dropoutOperating characteristics areaPotential treatment targetHead CTVisual markersIdentified patientsAutomated deep learning modelDataset of patientsRisk factorsHigh riskPatients
2023
Clinical Phenotyping with an Outcomes-driven Mixture of Experts for Patient Matching and Risk Estimation
Hurley N, Dhruva S, Desai N, Ross J, Ngufor C, Masoudi F, Krumholz H, Mortazavi B. Clinical Phenotyping with an Outcomes-driven Mixture of Experts for Patient Matching and Risk Estimation. ACM Transactions On Computing For Healthcare 2023, 4: 1-18. PMID: 37908872, PMCID: PMC10613929, DOI: 10.1145/3616021.Peer-Reviewed Original Research
2019
LCox: a tool for selecting genes related to survival outcomes using longitudinal gene expression data
Sun J, Herazo-Maya JD, Wang JL, Kaminski N, Zhao H. LCox: a tool for selecting genes related to survival outcomes using longitudinal gene expression data. Statistical Applications In Genetics And Molecular Biology 2019, 18: 20170060. PMID: 30759070, DOI: 10.1515/sagmb-2017-0060.Peer-Reviewed Original Research
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