2020
Serious Falls in Middle‐Aged Veterans: Development and Validation of a Predictive Risk Model
Womack JA, Murphy TE, Bathulapalli H, Smith A, Bates J, Jarad S, Redeker NS, Luther SL, Gill TM, Brandt CA, Justice AC. Serious Falls in Middle‐Aged Veterans: Development and Validation of a Predictive Risk Model. Journal Of The American Geriatrics Society 2020, 68: 2847-2854. PMID: 32860222, PMCID: PMC7744431, DOI: 10.1111/jgs.16773.Peer-Reviewed Original ResearchConceptsMiddle-aged veteransVeterans Health AdministrationOpioid useSerious fallsAlcohol Use Disorders Identification Test-Consumption scoresCategory-free net reclassification improvementIllicit substance use disordersMental health comorbiditiesPrescription opioid useMultivariable logistic regressionNet reclassification improvementSubstance use disordersQuality of lifeHazardous alcohol usePredictive risk modelChronic medicationsCohort studyHealth comorbiditiesNinth RevisionReclassification improvementGeriatric healthInjury codesHazardous alcoholInternational ClassificationUse disordersExploring supervised machine learning approaches to predicting Veterans Health Administration chiropractic service utilization
Coleman BC, Fodeh S, Lisi AJ, Goulet JL, Corcoran KL, Bathulapalli H, Brandt CA. Exploring supervised machine learning approaches to predicting Veterans Health Administration chiropractic service utilization. Chiropractic & Manual Therapies 2020, 28: 47. PMID: 32680545, PMCID: PMC7368704, DOI: 10.1186/s12998-020-00335-4.Peer-Reviewed Original ResearchConceptsSpinal pain conditionsService utilizationPain conditionsChiropractic careConservative interventionsChiropractic servicesVA chiropractic servicesRetrospective cohort studyHealthcare service utilizationHealthcare cost burdenLimited clinical utilityLower healthcare costsCohort entryCohort studyDiagnosis cohortPain statusPrimary outcomeChiropractic visitsClinical featuresUS adultsClinical utilityHealthcare costsDifferent clinical populationsVisitsClinical populations
2017
Classifying clinical notes with pain assessment using machine learning
Fodeh SJ, Finch D, Bouayad L, Luther SL, Ling H, Kerns RD, Brandt C. Classifying clinical notes with pain assessment using machine learning. Medical & Biological Engineering & Computing 2017, 56: 1285-1292. PMID: 29280092, PMCID: PMC6014866, DOI: 10.1007/s11517-017-1772-1.Peer-Reviewed Original ResearchConceptsPain care qualityPain assessmentClinical notesChronic painMusculoskeletal diagnosesSignificant public health problemCharacteristics of patientsIntensity of painType of painPublic health problemPain sitesPain complaintsPatient reportsPainPatientsHealth problemsCare qualityFiscal year 2011Health recordsMillions of peopleComplete dataClinical applicationDiagnosisDemographic variablesWide spectrum
2013
Complementary ensemble clustering of biomedical data
Fodeh SJ, Brandt C, Luong TB, Haddad A, Schultz M, Murphy T, Krauthammer M. Complementary ensemble clustering of biomedical data. Journal Of Biomedical Informatics 2013, 46: 436-443. PMID: 23454721, PMCID: PMC4007219, DOI: 10.1016/j.jbi.2013.02.001.Peer-Reviewed Original ResearchConceptsData modalitiesBiomedical dataEnsemble clusteringData mining methodsDifferent clustering approachesDifferent data modalitiesMultiple data modalitiesDifferent application areasNormalized mutual informationMicro-averaged precisionExtraction of informationBiomedical datasetsKmeans algorithmMining methodsClustering approachApplication areasMutual informationFinal clustersSingle modalityClusteringKmeansBetter performanceComplementary ensembleExperimental resultsAlgorithmFunctional Impairments as Symptoms in the Symptom Cluster Analysis of Patients Newly Diagnosed With Advanced Cancer
Fodeh SJ, Lazenby M, Bai M, Ercolano E, Murphy T, McCorkle R. Functional Impairments as Symptoms in the Symptom Cluster Analysis of Patients Newly Diagnosed With Advanced Cancer. Journal Of Pain And Symptom Management 2013, 46: 500-510. PMID: 23380336, PMCID: PMC4321795, DOI: 10.1016/j.jpainsymman.2012.09.011.Peer-Reviewed Original ResearchConceptsFunctional impairmentAdvanced cancerSymptom cluster analysisDays of diagnosisTime of diagnosisEarly cancer stagesHealth care providersLate-stage cancerSelf-reported symptomsSubsequent functional impairmentSelf-reported physical symptomsAdvanced gastrointestinalLung cancerCancer sitesCancer stageEarly recognitionCare providersDaily livingPhysical symptomsPatientsSymptomsInsomniaFunctional changesCancerImpairment