Featured Publications
Clinical Implementation of a Combined Artificial Intelligence and Natural Language Processing Quality Assurance Program for Pulmonary Nodule Detection in the Emergency Department Setting
Cavallo J, de Oliveira Santo I, Mezrich J, Forman H. Clinical Implementation of a Combined Artificial Intelligence and Natural Language Processing Quality Assurance Program for Pulmonary Nodule Detection in the Emergency Department Setting. Journal Of The American College Of Radiology 2023, 20: 438-445. PMID: 36736547, DOI: 10.1016/j.jacr.2022.12.016.Peer-Reviewed Original ResearchConceptsEmergency department settingPulmonary nodulesCT examinationsDepartment settingSecondary reviewNumber of patientsQuality assurance studyMedian timeEmergent settingPatient followImaging recommendationsAppropriate followMajority of reviewsRadiological reportsAssurance studyClinical implementationLung anatomyQuality assurance programPatientsSignificant delayNodulesFollowExaminationPulmonary nodule detectionNodule detection
2025
Radiologist, trainee, and logistical factors impacting the timeliness of CTA head and neck reporting in stroke code activations.
Zaree O, Nguyen J, de Oliveira Santo I, Kertam A, Rahmani S, Johnson J, Tu L. Radiologist, trainee, and logistical factors impacting the timeliness of CTA head and neck reporting in stroke code activations. American Journal Of Neuroradiology 2025, ajnr.a8660. PMID: 39832953, DOI: 10.3174/ajnr.a8660.Peer-Reviewed Original ResearchStroke code activationAttending radiologistsTimeliness of reportingEmergency department settingRadiologist characteristicsCare settingsMultivariate regression modelImprove workflow efficiencyDepartment settingStroke codeModifiable factorsDescriptive statisticsSecondary analysisCoding activitiesReport factorsPatient ageObservational studyWorkflow efficiencyShift typeMedian TATMultivariate regressionInterquartile rangeRegression modelsCTA reportsLogistical factors