2024
Using an artificial intelligence software improves emergency medicine physician intracranial haemorrhage detection to radiologist levels
Warman P, Warman A, Warman R, Degnan A, Blickman J, Smith D, McHale P, Coburn Z, McCormick S, Chowdhary V, Dash D, Sangal R, Vadhan J, Bueso T, Windisch T, Neves G. Using an artificial intelligence software improves emergency medicine physician intracranial haemorrhage detection to radiologist levels. Emergency Medicine Journal 2024, 41: 298-303. PMID: 38233106, DOI: 10.1136/emermed-2023-213158.Peer-Reviewed Original ResearchCranial CT scanEmergency physiciansIntracranial haemorrhageBoard-certified emergency physiciansCT scanYears of practice experienceNon-contrast cranial CT scansED physiciansClinical careImaging ReportingEP cohortArtificial intelligenceReader accuracyNon-contrastPatient outcomesRadiologistsRandom orderPhysiciansPatientsCohort
2022
Deep Learning System Boosts Radiologist Detection of Intracranial Hemorrhage
Warman R, Warman A, Warman P, Degnan A, Blickman J, Chowdhary V, Dash D, Sangal R, Vadhan J, Bueso T, Windisch T, Neves G, Degnan A, Blickman J, Vadhan J. Deep Learning System Boosts Radiologist Detection of Intracranial Hemorrhage. Cureus 2022, 14: e30264. PMID: 36381767, PMCID: PMC9653089, DOI: 10.7759/cureus.30264.Peer-Reviewed Original ResearchIntracranial hemorrhage subtypesIntracranial hemorrhageCranial computed tomographyInter-reader agreementDetect intracranial hemorrhageCohort of radiologistsPerformance of radiologistsImprove patient outcomesReduce misdiagnosisRadiologistsPatient outcomesRadiologist's abilityMedical treatmentSubtypesPositive outcomesOutcomes