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
2015
Correlation between Flat Panel Computed Tomography and Conventional Computed tomography for Detection of Post Endovascular Treatment Hemorrhages. (P4.300)
Khan A, Payabvash S, Qureshi M, Saeed O, Suri M, Qureshi A. Correlation between Flat Panel Computed Tomography and Conventional Computed tomography for Detection of Post Endovascular Treatment Hemorrhages. (P4.300). Neurology 2015, 84 DOI: 10.1212/wnl.84.14_supplement.p4.300.Peer-Reviewed Original Research