2019
Scoring of Coronary Artery Disease Characteristics on Coronary CT Angiograms by Using Machine Learning
Johnson KM, Johnson HE, Zhao Y, Dowe DA, Staib LH. Scoring of Coronary Artery Disease Characteristics on Coronary CT Angiograms by Using Machine Learning. Radiology 2019, 292: 182061. PMID: 31237495, DOI: 10.1148/radiol.2019182061.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overComputed Tomography AngiographyCoronary AngiographyCoronary Artery DiseaseCoronary VesselsFemaleHumansImage Interpretation, Computer-AssistedMachine LearningMaleMiddle AgedPredictive Value of TestsReproducibility of ResultsRisk FactorsSeverity of Illness IndexYoung AdultConceptsCoronary CT angiographyCoronary Artery Disease ReportingNonfatal myocardial infarctionHeart disease deathCT angiographyCause mortalityDisease deathsMyocardial infarctionCoronary heart disease deathDisease reportingCoronary artery diseaseNational Death IndexData System scoreCardiovascular eventsCoronary deathAdverse eventsArtery diseaseCoronary diseaseDeath IndexCoronary segmentsPrognostic informationVessel scorePatientsSystem scoreSubsequent death
2016
Brain responses to biological motion predict treatment outcome in young children with autism
Yang D, Pelphrey KA, Sukhodolsky DG, Crowley MJ, Dayan E, Dvornek NC, Venkataraman A, Duncan J, Staib L, Ventola P. Brain responses to biological motion predict treatment outcome in young children with autism. Translational Psychiatry 2016, 6: e948-e948. PMID: 27845779, PMCID: PMC5314125, DOI: 10.1038/tp.2016.213.Peer-Reviewed Original ResearchConceptsAutism spectrum disorderYoung childrenSocial information processingMultivariate pattern analysisMotivation/rewardBiological motionCore deficitComplex neurodevelopmental disorderBrain responsesResponse treatmentSpectrum disorderNeurobiological markersNeural predictorsInformation processingBehavioral interventionsIndividual childrenNeurodevelopmental disordersCurrent findingsNeural circuitsBehavioral deficitsEarly childhoodChildrenUnsuccessful interventionsNeurobiomarkersPattern analysis
2012
Gender-based divergence of cardiovascular outcomes in asymptomatic patients with type 2 diabetes: Results from the DIAD study
Tandon S, Wackers F, Inzucchi SE, Bansal S, Staib LH, Chyun DA, Davey JA, Young LH. Gender-based divergence of cardiovascular outcomes in asymptomatic patients with type 2 diabetes: Results from the DIAD study. Diabetes And Vascular Disease Research 2012, 9: 124-130. PMID: 22228772, DOI: 10.1177/1479164111431470.Peer-Reviewed Original ResearchMeSH KeywordsAgedAsymptomatic DiseasesCanadaCardiovascular DiseasesDiabetes ComplicationsDiabetes Mellitus, Type 2FemaleHumansIncidenceKaplan-Meier EstimateMaleMass ScreeningMiddle AgedMyocardial Perfusion ImagingPredictive Value of TestsPrognosisProspective StudiesRisk AssessmentRisk FactorsSex FactorsTime FactorsUnited StatesConceptsType 2 diabetesMyocardial perfusion imagingCardiovascular outcomesStress myocardial perfusion imagingAsymptomatic Diabetics (DIAD) studyBetter cardiac outcomesHigh-risk womenCoronary artery diseaseHigh-risk menDetection of ischemiaMPI abnormalitiesAsymptomatic patientsAsymptomatic menCardiac eventsCardiac outcomesArtery diseaseAsymptomatic womenAbnormal screeningDiabetic studyPerfusion imagingDIAD studyWomenMenDiabetesOutcomes
2001
Automated measurement of latent morphological features in the human corpus callosum
Peterson B, Feineigle P, Staib L, Gore J. Automated measurement of latent morphological features in the human corpus callosum. Human Brain Mapping 2001, 12: 232-245. PMID: 11241874, PMCID: PMC6871880, DOI: 10.1002/1097-0193(200104)12:4<232::aid-hbm1018>3.0.co;2-j.Peer-Reviewed Original ResearchConceptsCorpus callosumSubject characteristicsYears of ageHuman corpus callosumPatient groupCallosum sizeHealthy subjectsMRI scansVentricular volumeCallosumMidsagittal planeFactor scoresNeural correlatesConstruct validityFactor-based analysisConventional measuresFuture studiesMorphological featuresAgePredictive validitySubjectsScoresNormal developmentVarimax rotationFactors