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
2015
A journal's role in resource sharing and reproducibility
Ohno-Machado L. A journal's role in resource sharing and reproducibility. Journal Of The American Medical Informatics Association 2015, 22: 491-491. PMID: 26048962, DOI: 10.1093/jamia/ocv057.Commentaries, Editorials and Letters
2013
Comparison of four prediction models to discriminate benign from malignant vertebral compression fractures according to MRI feature analysis.
Thawait S, Kim J, Klufas R, Morrison W, Flanders A, Carrino J, Ohno-Machado L. Comparison of four prediction models to discriminate benign from malignant vertebral compression fractures according to MRI feature analysis. American Journal Of Roentgenology 2013, 200: 493-502. PMID: 23436836, DOI: 10.2214/ajr.11.7192.Peer-Reviewed Original ResearchAdultAgedAged, 80 and overAlgorithmsCohort StudiesComputer SimulationDiagnosis, DifferentialFemaleFractures, CompressionHumansImage EnhancementImage Interpretation, Computer-AssistedMagnetic Resonance ImagingMaleMiddle AgedModels, BiologicalNeoplasmsPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificitySpinal FracturesYoung Adult
2012
Doubly Optimized Calibrated Support Vector Machine (DOC-SVM): An Algorithm for Joint Optimization of Discrimination and Calibration
Jiang X, Menon A, Wang S, Kim J, Ohno-Machado L. Doubly Optimized Calibrated Support Vector Machine (DOC-SVM): An Algorithm for Joint Optimization of Discrimination and Calibration. PLOS ONE 2012, 7: e48823. PMID: 23139819, PMCID: PMC3490990, DOI: 10.1371/journal.pone.0048823.Peer-Reviewed Original ResearchMeSH KeywordsArea Under CurveBreast NeoplasmsCalibrationComputer SimulationDatabases, GeneticFemaleHumansModels, BiologicalProbabilityReproducibility of ResultsROC CurveSupport Vector Machine
2008
Validation of an Automated Safety Surveillance System with Prospective, Randomized Trial Data
Matheny M, Morrow D, Ohno-Machado L, Cannon C, Sabatine M, Resnic F. Validation of an Automated Safety Surveillance System with Prospective, Randomized Trial Data. Medical Decision Making 2008, 29: 247-256. PMID: 19015285, PMCID: PMC2743924, DOI: 10.1177/0272989x08327110.Peer-Reviewed Original ResearchMeSH KeywordsBayes TheoremData Interpretation, StatisticalDecision Support TechniquesFibrinolytic AgentsHumansIntracranial HemorrhagesMulticenter Studies as TopicMyocardial InfarctionRandomized Controlled Trials as TopicReproducibility of ResultsRetrospective StudiesSafety ManagementSentinel SurveillanceConceptsIntervention armMortality rateEvent ratesTrial BTrial AMajor bleeding ratesOutcomes Surveillance SystemIntracranial hemorrhage rateCumulative event rateRandomized trial dataEvent-rate analysisSafety surveillance systemSurveillance systemAdverse eventsMulticenter trialHemorrhage rateMonth 14Bleeding rateControl armClinical trialsTrial B.Trial dataTrialsObserved event ratesMonths
2007
Effects of SVM parameter optimization on discrimination and calibration for post-procedural PCI mortality
Matheny M, Resnic F, Arora N, Ohno-Machado L. Effects of SVM parameter optimization on discrimination and calibration for post-procedural PCI mortality. Journal Of Biomedical Informatics 2007, 40: 688-697. PMID: 17600771, PMCID: PMC2170520, DOI: 10.1016/j.jbi.2007.05.008.Peer-Reviewed Original ResearchConceptsSupport vector machineRadial Basis Kernel Support Vector MachineKernel support vector machineCross-entropy errorSVM parameter optimizationUnseen test dataSVM kernel typesTraining dataVector machineEvolutionary algorithmGrid searchMean squared errorKernel typeMachineOptimization methodPrediction modelNumber of methodsParameter optimizationTest dataMedical applicationsOptimization parametersMortality prediction modelAlgorithmBest modelApplications
2006
A sequence-oriented comparison of gene expression measurements across different hybridization-based technologies
Kuo W, Liu F, Trimarchi J, Punzo C, Lombardi M, Sarang J, Whipple M, Maysuria M, Serikawa K, Lee S, McCrann D, Kang J, Shearstone J, Burke J, Park D, Wang X, Rector T, Ricciardi-Castagnoli P, Perrin S, Choi S, Bumgarner R, Kim J, Short G, Freeman M, Seed B, Jensen R, Church G, Hovig E, Cepko C, Park P, Ohno-Machado L, Jenssen T. A sequence-oriented comparison of gene expression measurements across different hybridization-based technologies. Nature Biotechnology 2006, 24: 832-840. PMID: 16823376, DOI: 10.1038/nbt1217.Peer-Reviewed Original ResearchApproximation 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
2004
The Goodman-Kruskal coefficient and its applications in genetic diagnosis of cancer
Jaroszewicz S, Simovici D, Kuo W, Ohno-Machado L. The Goodman-Kruskal coefficient and its applications in genetic diagnosis of cancer. IEEE Transactions On Biomedical Engineering 2004, 51: 1095-1102. PMID: 15248526, DOI: 10.1109/tbme.2004.827267.Peer-Reviewed Original ResearchDiagnostic accuracy of chest X-rays acquired using a digital camera for low-cost teleradiology
Szot A, Jacobson F, Munn S, Jazayeri D, Nardell E, Harrison D, Drosten R, Ohno-Machado L, Smeaton L, Fraser H. Diagnostic accuracy of chest X-rays acquired using a digital camera for low-cost teleradiology. International Journal Of Medical Informatics 2004, 73: 65-73. PMID: 15036080, DOI: 10.1016/j.ijmedinf.2003.10.002.Peer-Reviewed Original Research
2002
Analysis of matched mRNA measurements from two different microarray technologies
Kuo W, Jenssen T, Butte A, Ohno-Machado L, Kohane I. Analysis of matched mRNA measurements from two different microarray technologies. Bioinformatics 2002, 18: 405-412. PMID: 11934739, DOI: 10.1093/bioinformatics/18.3.405.Peer-Reviewed Original Research
2000
Using electronic data to predict the probability of true bacteremia from positive blood cultures.
Wang S, Kuperman G, Ohno-Machado L, Onderdonk A, Sandige H, Bates D. Using electronic data to predict the probability of true bacteremia from positive blood cultures. AMIA Annual Symposium Proceedings 2000, 893-7. PMID: 11080013, PMCID: PMC2243892.Peer-Reviewed Original ResearchConceptsPositive blood culturesClinical prediction ruleBlood culturesTreatment decisionsTrue bacteremiaCulture resultsPositive blood culture resultsPrediction rulePaper chart reviewProbability of bacteremiaBlood culture resultsInfectious disease expertsAppropriate treatment decisionsLogistic regression modelsRevalidation studyChart reviewDisease expertsOne-year periodBacteremiaPhysiciansRegression modelsTrue positivesPatientsHospitalHousestaff