2023
Value Proposition of FDA-Approved Artificial Intelligence Algorithms for Neuroimaging
Bajaj S, Khunte M, Moily N, Payabvash S, Wintermark M, Gandhi D, Malhotra A. Value Proposition of FDA-Approved Artificial Intelligence Algorithms for Neuroimaging. Journal Of The American College Of Radiology 2023, 20: 1241-1249. PMID: 37574094, DOI: 10.1016/j.jacr.2023.06.034.Peer-Reviewed Original ResearchConceptsArtificial intelligence algorithmsAI algorithmsIntelligence algorithmsValue propositionUser timeAI developersMost vendorsProduct informationDevelopersAlgorithmVendorsProduct websitesDeveloper websitesWebsitesUser testimonialsCentral databaseTechnologyDatabaseInformationAIDevicesAdoptionPropositionCostArtificial Intelligence for Neuroimaging and Musculoskeletal Radiology: Overview of Current Commercial Algorithms
Berson E, Aboian M, Malhotra A, Payabvash S. Artificial Intelligence for Neuroimaging and Musculoskeletal Radiology: Overview of Current Commercial Algorithms. Seminars In Roentgenology 2023, 58: 178-183. PMID: 37087138, PMCID: PMC10122717, DOI: 10.1053/j.ro.2023.03.002.Peer-Reviewed Original Research
2019
White Matter Connectome Edge Density in Children with Autism Spectrum Disorders: Potential Imaging Biomarkers Using Machine-Learning Models
Payabvash S, Palacios E, Owen JP, Wang MB, Tavassoli T, Gerdes M, Brandes-Aitken A, Cuneo D, Marco E, Mukherjee P. White Matter Connectome Edge Density in Children with Autism Spectrum Disorders: Potential Imaging Biomarkers Using Machine-Learning Models. Brain Connectivity 2019, 9: 209-220. PMID: 30661372, PMCID: PMC6444925, DOI: 10.1089/brain.2018.0658.Peer-Reviewed Original Research
2018
A user-guided tool for semi-automated cerebral microbleed detection and volume segmentation: Evaluating vascular injury and data labelling for machine learning
Morrison MA, Payabvash S, Chen Y, Avadiappan S, Shah M, Zou X, Hess CP, Lupo JM. A user-guided tool for semi-automated cerebral microbleed detection and volume segmentation: Evaluating vascular injury and data labelling for machine learning. NeuroImage Clinical 2018, 20: 498-505. PMID: 30140608, PMCID: PMC6104340, DOI: 10.1016/j.nicl.2018.08.002.Peer-Reviewed Original ResearchConceptsData labelingTraining dataHigh-level feature extractionVolume segmentationComputer-aided detection algorithmComputer-aided detection methodsGround truth labelingCerebral microbleed detectionFalse positivesMachine learningFeature extractionSegmentation resultsDetection algorithmSophisticated machineTime usersAlgorithm performanceCMB detectionComputer aidMicrobleed detectionSegmentationTest setDetection methodSuperior performanceExtensive research effortsMachine
2013
Admission Insular Infarction >25% Is the Strongest Predictor of Large Mismatch Loss in Proximal Middle Cerebral Artery Stroke
Kamalian S, Kemmling A, Borgie RC, Morais LT, Payabvash S, Franceschi AM, Kamalian S, Yoo AJ, Furie KL, Lev MH. Admission Insular Infarction >25% Is the Strongest Predictor of Large Mismatch Loss in Proximal Middle Cerebral Artery Stroke. Stroke 2013, 44: 3084-3089. PMID: 23988643, PMCID: PMC3894265, DOI: 10.1161/strokeaha.113.002260.Peer-Reviewed Original ResearchConceptsInfarct volumeInsular infarctionHealth Stroke Scale scoreMiddle cerebral artery infarctConsecutive acute stroke patientsMiddle cerebral artery strokeProximal middle cerebral arteryRapid reperfusion therapyTreatment-eligible patientsAcute stroke patientsStroke Scale scoreFinal infarct volumeMiddle cerebral arteryStrongest predictorCharacteristic curve areaExcellent interobserver agreementDiffusion-weighted imaging imagesBinary logistic regressionArtery infarctInfarct progressionOcclusive strokePenumbral tissueReperfusion therapyCollateral scoreIndependent predictors
2011
CT Perfusion Mean Transit Time Maps Optimally Distinguish Benign Oligemia from True “At-Risk” Ischemic Penumbra, but Thresholds Vary by Postprocessing Technique
Kamalian S, Kamalian S, Konstas AA, Maas MB, Payabvash S, Pomerantz SR, Schaefer PW, Furie KL, González RG, Lev MH. CT Perfusion Mean Transit Time Maps Optimally Distinguish Benign Oligemia from True “At-Risk” Ischemic Penumbra, but Thresholds Vary by Postprocessing Technique. American Journal Of Neuroradiology 2011, 33: 545-549. PMID: 22194372, PMCID: PMC3746025, DOI: 10.3174/ajnr.a2809.Peer-Reviewed Original ResearchConceptsAcute stroke patientsLarge vessel occlusionBenign oligemiaStroke patientsIschemic penumbraCTP parametersRelative cerebral blood flowConsecutive stroke patientsHours of onsetCerebral blood flowMean transit time mapsCharacteristic curve analysisTransit time mapsUninvolved hemisphereRadiographic evidenceThrombolytic therapyFinal infarctVessel occlusionRelative MTTBlood flowCTP mapsPerfusion parametersOligemiaReperfusionPatients
2010
Predicting Language Improvement in Acute Stroke Patients Presenting with Aphasia: A Multivariate Logistic Model Using Location-Weighted Atlas-Based Analysis of Admission CT Perfusion Scans
Payabvash S, Kamalian S, Fung S, Wang Y, Passanese J, Kamalian S, Souza LC, Kemmling A, Harris GJ, Halpern EF, González RG, Furie KL, Lev MH. Predicting Language Improvement in Acute Stroke Patients Presenting with Aphasia: A Multivariate Logistic Model Using Location-Weighted Atlas-Based Analysis of Admission CT Perfusion Scans. American Journal Of Neuroradiology 2010, 31: 1661-1668. PMID: 20488905, PMCID: PMC3640318, DOI: 10.3174/ajnr.a2125.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsAphasiaBrainComputer SimulationFemaleHumansLogistic ModelsMaleModels, NeurologicalMultivariate AnalysisPattern Recognition, AutomatedPerfusion ImagingPrognosisRadiographic Image Interpretation, Computer-AssistedReproducibility of ResultsSensitivity and SpecificityStrokeSubtraction TechniqueTomography, X-Ray ComputedConceptsBrain CTPNIHSS scoreStroke onsetFunctional outcomeFirst-time ischemic strokeProximal cerebral artery occlusionMultiple logistic regression analysisMultivariate logistic regression modelMultivariate modelDischarge NIHSS scoreTotal NIHSS scoreAcute stroke patientsCerebral artery occlusionTime of dischargeCT perfusion imagingLogistic regression analysisMultivariate logistic modelCT perfusion scansLogistic regression modelsAdmission CTAArtery occlusionInfarct volumeIschemic strokeClinical predictorsConsecutive patients