2021
Machine Learning-based Prediction Models for Diagnosis and Prognosis in Inflammatory Bowel Diseases: A Systematic Review
Nguyen N, Picetti D, Dulai P, Jairath V, Sandborn W, Ohno-Machado L, Chen P, Singh S. Machine Learning-based Prediction Models for Diagnosis and Prognosis in Inflammatory Bowel Diseases: A Systematic Review. Journal Of Crohn's And Colitis 2021, 16: 398-413. PMID: 34492100, PMCID: PMC8919806, DOI: 10.1093/ecco-jcc/jjab155.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsInflammatory bowel diseaseBowel diseaseClinical dataHigh riskRisk predictionSystematic reviewAcute severe ulcerative colitisLongitudinal disease activitySevere ulcerative colitisAdverse clinical outcomesBias assessment toolRisk of biasAvailable clinical dataMachine learning-based prediction modelsPrediction model RiskDisease activityCohort studyUlcerative colitisClinical outcomesTreatment responseClinical applicabilityLearning-based prediction modelsExternal validationPatientsRiskPredictive Analytics for Glaucoma Using Data From the All of Us Research Program
Baxter S, Saseendrakumar B, Paul P, Kim J, Bonomi L, Kuo T, Loperena R, Ratsimbazafy F, Boerwinkle E, Cicek M, Clark C, Cohn E, Gebo K, Mayo K, Mockrin S, Schully S, Ramirez A, Ohno-Machado L, Investigators A. Predictive Analytics for Glaucoma Using Data From the All of Us Research Program. American Journal Of Ophthalmology 2021, 227: 74-86. PMID: 33497675, PMCID: PMC8184631, DOI: 10.1016/j.ajo.2021.01.008.Peer-Reviewed Original ResearchConceptsGlaucoma surgeryPrimary open-angle glaucomaOphthalmic researchSingle-center cohortElectronic health record dataMultivariable logistic regressionSingle-center dataOpen-angle glaucomaHealth record dataMean ageClaims dataUs Research ProgramLogistic regressionSurgeryRecord dataOphthalmic imagingCharacteristic curveExternal validationGlaucomaCohortAUCSingle-center model
2020
A tutorial on calibration measurements and calibration models for clinical prediction models
Huang Y, Li W, Macheret F, Gabriel R, Ohno-Machado L. A tutorial on calibration measurements and calibration models for clinical prediction models. Journal Of The American Medical Informatics Association 2020, 27: 621-633. PMID: 32106284, PMCID: PMC7075534, DOI: 10.1093/jamia/ocz228.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus Statements
2019
Machine Learning-Based Predictive Modeling of Surgical Intervention in Glaucoma Using Systemic Data From Electronic Health Records
Baxter S, Marks C, Kuo T, Ohno-Machado L, Weinreb R. Machine Learning-Based Predictive Modeling of Surgical Intervention in Glaucoma Using Systemic Data From Electronic Health Records. American Journal Of Ophthalmology 2019, 208: 30-40. PMID: 31323204, PMCID: PMC6888922, DOI: 10.1016/j.ajo.2019.07.005.Peer-Reviewed Original ResearchConceptsPrimary open-angle glaucomaElectronic health recordsMultivariable logistic regressionSurgical interventionGlaucoma surgeryPOAG patientsSystemic dataHigher mean systolic blood pressureMean systolic blood pressureNon-opioid analgesic medicationsLogistic regressionCertain medication classesEye-specific dataHealth recordsRisk of progressionSystolic blood pressureOpen-angle glaucomaSingle academic institutionAnti-hyperlipidemic medicationsAnalgesic medicationMedication classesProgressive diseaseBlood pressureCalcium blockersOphthalmic medications
2017
A Predictive Model for Extended Postanesthesia Care Unit Length of Stay in Outpatient Surgeries
Gabriel R, Waterman R, Kim J, Ohno-Machado L. A Predictive Model for Extended Postanesthesia Care Unit Length of Stay in Outpatient Surgeries. Anesthesia & Analgesia 2017, 124: 1529-1536. PMID: 28079580, DOI: 10.1213/ane.0000000000001827.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAge FactorsAgedAged, 80 and overAmbulatory Surgical ProceduresAnesthesiaChildChild, PreschoolCritical CareFemaleForecastingHumansHypertensionInfantInfant, NewbornIntensive Care UnitsLength of StayLogistic ModelsMaleMiddle AgedModels, StatisticalObesity, MorbidPostoperative CareRisk FactorsROC CurveYoung AdultConceptsPACU lengthPostanesthesia care unit lengthPrimary anesthesia typePostanesthesia care unitHosmer-Lemeshow testLogistic regression modelsAnesthesia typeMorbid obesityCare unitHL testOutpatient surgeryOutpatient procedureSingle institutionHigher oddsNonsignificant P valuesStayPatientsSurgical specialtiesROC curveGood calibrationCharacteristic curveExcellent discriminationAUC valuesP-valueBackward eliminationA risk prediction score for acute kidney injury in the intensive care unit
Malhotra R, Kashani K, Macedo E, Kim J, Bouchard J, Wynn S, Li G, Ohno-Machado L, Mehta R. A risk prediction score for acute kidney injury in the intensive care unit. Nephrology Dialysis Transplantation 2017, 32: 814-822. PMID: 28402551, DOI: 10.1093/ndt/gfx026.Peer-Reviewed Original ResearchConceptsAcute kidney injuryIntensive care unitAcute risk factorsRisk score modelICU admissionKidney injuryCare unitValidation cohortKidney diseaseRisk factorsTest cohortTreatment of AKIAtherosclerotic coronary vascular diseaseMulticenter prospective cohort studyGlobal Outcomes criteriaChronic kidney diseaseHigh-risk patientsProspective cohort studyChronic liver diseaseCongestive heart failureTime of screeningCoronary vascular diseaseRisk prediction scoreEarly therapeutic interventionExternal validation cohort
2015
A system to build distributed multivariate models and manage disparate data sharing policies: implementation in the scalable national network for effectiveness research
Meeker D, Jiang X, Matheny M, Farcas C, D’Arcy M, Pearlman L, Nookala L, Day M, Kim K, Kim H, Boxwala A, El-Kareh R, Kuo G, Resnic F, Kesselman C, Ohno-Machado L. A system to build distributed multivariate models and manage disparate data sharing policies: implementation in the scalable national network for effectiveness research. Journal Of The American Medical Informatics Association 2015, 22: 1187-1195. PMID: 26142423, PMCID: PMC4639714, DOI: 10.1093/jamia/ocv017.Peer-Reviewed Original ResearchConceptsFederated networkData sharing policiesParallel computation methodSharing policiesPolicy management systemData exchange policiesData storage requirementsWeb servicesNetwork queriesQuery functionalityComputation resourcesFederated modelGraphical interfaceData transportCentralized networkStorage requirementsNetwork participantsManagement systemQueriesNetworkComputation methodNew featuresMultivariate statistical estimationDifferent state lawsImportant new featureGrid multi-category response logistic models
Wu Y, Jiang X, Wang S, Jiang W, Li P, Ohno-Machado L. Grid multi-category response logistic models. BMC Medical Informatics And Decision Making 2015, 15: 10. PMID: 25886151, PMCID: PMC4342889, DOI: 10.1186/s12911-015-0133-y.Peer-Reviewed Original ResearchMeSH KeywordsClinical Decision-MakingConfidentialityHumansInformation DisseminationLogistic ModelsModels, StatisticalConceptsGrid modelLikelihood estimation problemClassification performance evaluationReal data setsGrid computingEstimation problemTypes of modelsGrid computationGrid methodPrivacyResponse modelCentralized modelMulti-center dataSuch decompositionsFit assessmentFitting methodLinear modelPerformance evaluationModel constructionData setsModel assumptionsIndividual observationsPractical solutionComputationResultsSimulation results
2006
Approximation properties of haplotype tagging
Vinterbo S, Dreiseitl S, Ohno-Machado L. Approximation properties of haplotype tagging. BMC Bioinformatics 2006, 7: 8. PMID: 16401341, PMCID: PMC1395335, DOI: 10.1186/1471-2105-7-8.Peer-Reviewed Original ResearchConceptsApproximation propertiesCombinatorial optimization problemsOptimization problemImplementable algorithmComputational effortSolution qualityTerms of complexitySimple algorithmSize m.Population membersSingle processor machineAlgorithmProblemAsymptoticsApproximationProcessor machineHaplotype taggingNPsUnique identification
2005
Representation in stochastic search for phylogenetic tree reconstruction
Weber G, Ohno-Machado L, Shieber S. Representation in stochastic search for phylogenetic tree reconstruction. Journal Of Biomedical Informatics 2005, 39: 43-50. PMID: 16359929, DOI: 10.1016/j.jbi.2005.11.001.Peer-Reviewed Original ResearchCombining Classifiers Using Their Receiver Operating Characteristics and Maximum Likelihood Estimation
Haker S, Wells W, Warfield S, Talos I, Bhagwat J, Goldberg-Zimring D, Mian A, Ohno-Machado L, Zou K. Combining Classifiers Using Their Receiver Operating Characteristics and Maximum Likelihood Estimation. Lecture Notes In Computer Science 2005, 8: 506-514. PMID: 16685884, PMCID: PMC3681096, DOI: 10.1007/11566465_63.Peer-Reviewed Original Research
2004
A greedy algorithm for supervised discretization
Butterworth R, Simovici D, Santos G, Ohno-Machado L. A greedy algorithm for supervised discretization. Journal Of Biomedical Informatics 2004, 37: 285-292. PMID: 15465481, DOI: 10.1016/j.jbi.2004.07.006.Peer-Reviewed Original Research
2001
Modeling Medical Prognosis: Survival Analysis Techniques
Ohno-Machado L. Modeling Medical Prognosis: Survival Analysis Techniques. Journal Of Biomedical Informatics 2001, 34: 428-439. PMID: 12198763, DOI: 10.1006/jbin.2002.1038.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsEffects of Case Removal in Prognostic Models
Ohno-Machado L, Vinterbo S. Effects of Case Removal in Prognostic Models. Methods Of Information In Medicine 2001, 40: 32-38. PMID: 11310157, DOI: 10.1055/s-0038-1634461.Peer-Reviewed Original Research
2000
Major complications after angioplasty in patients with chronic renal failure: a comparison of predictive models.
Lacson R, Ohno-Machado L. Major complications after angioplasty in patients with chronic renal failure: a comparison of predictive models. AMIA Annual Symposium Proceedings 2000, 457-61. PMID: 11079925, PMCID: PMC2243840.Peer-Reviewed Original ResearchConceptsPercutaneous transluminal coronary angioplastyEnd-stage renal diseaseChronic renal failureMajor complicationsRenal failureCongestive heart failurePatient risk factorsTransluminal coronary angioplastyLogistic regression modelsCoronary angioplastyHeart failureRenal diseasePoor outcomeMyocardial infarctionRisk factorsPrior historyPresence of shockComplicationsLogistic regressionPatientsDiscriminatory abilityDemographic characteristicsAngioplastyRegression modelsStandard logistic regression model
1998
Comparison of multiple prediction models for ambulation following spinal cord injury.
Rowland T, Ohno-Machado L, Ohrn A. Comparison of multiple prediction models for ambulation following spinal cord injury. AMIA Annual Symposium Proceedings 1998, 528-32. PMID: 9929275, PMCID: PMC2232380.Peer-Reviewed Original Research
1995
Hierarchical neural networks for survival analysis.
Ohno-Machado L, Walker M, Musen M. Hierarchical neural networks for survival analysis. Medinfo. 1995, 8 Pt 1: 828-32. PMID: 8591339.Peer-Reviewed Original ResearchConceptsNeural networkHierarchical neural networkHierarchical systemHierarchical modelHierarchical architectureDiscrete variablesNetworkData setsNonhierarchical modelTraditional methodsMedical applicationsAccurate predictionNumber of eventsArchitectureSystemTime-dependent variablesModelDataFirst time intervalTime intervalPredictionSetVariables