grant
Predicting Cognitive Outcomes from Stroke Using Lesion Location
Organization UNIVERSITY OF IOWALocation IOWA CITY, UNITED STATESPosted 5 Feb 2026Deadline 30 Nov 2030
NIHUS FederalResearch GrantFY202621+ years oldAddressAdultAdult HumanAffectAlgorithmsAnatomic SitesAnatomic structuresAnatomyAnxietyApoplexyAttentionBlood VesselsBrainBrain MappingBrain Nervous SystemBrain Vascular AccidentBrain regionCerebral StrokeCerebrovascular ApoplexyCerebrovascular StrokeChronicClinicalClinical ManagementCognitionCognitiveCognitive DisturbanceCognitive ImpairmentCognitive declineCognitive deficitsCognitive function abnormalComputer Software DevelopmentComputer Software EngineeringDataData BasesDatabasesDevelopmentDisablingDisturbance in cognitionEarly InterventionEncephalonEngineeringFDA approvedFoundationsGoalsHeadHealthHomeImageImaging DeviceImaging InstrumentImaging ToolImpaired cognitionIndividualInterventionIowaIschemic StrokeKnowledgeLanguageLesionLifeLinkLocationMR ImagingMR TomographyMRIMRIsMagnetic Resonance ImagingManualsMapsMedical Imaging, Magnetic Resonance / Nuclear Magnetic ResonanceMedical RehabilitationMemoryMethodsModalityModelingNMR ImagingNMR TomographyNeurologistNuclear Magnetic Resonance ImagingOutcomeOutcome MeasurePatient outcomePatient-Centered OutcomesPatient-Focused OutcomesPatientsPatternPerformancePositionPositioning AttributePredictive ValueProbabilistic ModelsProbability ModelsProspective cohortRecoveryRegistriesRehabilitationRehabilitation therapyReportingResearchResearch ResourcesResourcesRiskSamplingSeriesSeveritiesSiteSoftware EngineeringSourceSpecialistStatistical ModelsStrokeStructure-Activity RelationshipSymptomsTestingTranslatingUniversitiesValidationZeugmatographyacute cerebrovascular accidentacute strokeadulthoodalgorithm trainingautomated algorithmautomatic algorithmbrain MR imagingbrain MRIbrain attackbrain magnetic resonance imagingcerebral MR imagingcerebral MRIcerebral magnetic resonance imagingcerebral vascular accidentcerebrovascular accidentchemical structure functionclinical imagingclinical practiceclinical trial readinesscognitive defectscognitive dysfunctioncognitive function after strokecognitive losscognitive outcome after strokecognitive outcome from strokecognitive outcome of strokecognitive performancecohortcomputer based predictionconnectomeconnectome dataconnectomic datadata basedata to traindataset to traindeep learningdeep learning methoddeep learning strategydemographicsdesigndesigningdevelopmentaldisabilityexperiencefunctional independencehomesimagingimaging biomarkerimaging markerimaging-based biological markerimaging-based biomarkerimaging-based markerimprovedindividualized predictionsinnovateinnovationinnovativeloved onesmachine learning based modelmachine learning modelmeasurable outcomemulti-modalitymultimodalitynetwork modelsneural imagingneuro-imagingneuroimagingneurological imagingnew approachesnovelnovel approachesnovel strategiesnovel strategyoutcome measurementoutcome predictionpatient oriented outcomespersonalized predictionspost stroke cognitive functionpost-stroke cognitive outcomepredictive modelingprognosticationprogramsprospectivepublic health relevancerehab strategyrehab therapyrehabilitation strategyrehabilitativerehabilitative therapysegmentation algorithmstatistical linear mixed modelsstatistical linear modelsstroke cognitive outcomestrokedstrokesstructure function relationshiptooltraining datatraining datasetsvalidationsvascular
Description preview
Abstract
Having a stroke is a frightening experience for the individual and their loved ones. A major source of anxiety is
not knowing what stroke-related deficits will persist – will my loved one ever be able to talk again or understand
me? The likelihood for recovery is estimated by the treating neurologist or rehabilitation specialist based on…
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