2018
A Scalable Privacy-preserving Data Generation Methodology for Exploratory Analysis.
Vaidya J, Shafiq B, Asani M, Adam N, Jiang X, Ohno-Machado L. A Scalable Privacy-preserving Data Generation Methodology for Exploratory Analysis. AMIA Annual Symposium Proceedings 2018, 2017: 1695-1704. PMID: 29854240, PMCID: PMC5977652.Peer-Reviewed Original ResearchConceptsPrivacy-preserving approachData management systemBig dataBiomedical datasetsClassification taskBiomedical dataContext of regressionManagement systemSynthetic dataGeneration methodologyEssential problemResearch tasksAdditional datasetsDatasetTaskSignificant effortsDirect accessFirstorder approximationDataParticular typeAccessPrecision medicine
2017
Information retrieval for biomedical datasets: the 2016 bioCADDIE dataset retrieval challenge
Roberts K, Gururaj A, Chen X, Pournejati S, Hersh W, Demner-Fushman D, Ohno-Machado L, Cohen T, Xu H. Information retrieval for biomedical datasets: the 2016 bioCADDIE dataset retrieval challenge. Database 2017, 2017: bax068. DOI: 10.1093/database/bax068.Peer-Reviewed Original ResearchBiomedical datasetsRetrieval challengesInformation retrieval techniquesAdvanced query processingBiomedical data repositoriesAdvanced retrieval methodsQuery processingInformation retrievalTest queriesRetrieval systemRank frameworkRetrieval approachRetrieval techniquesData repositoryRetrieval methodTop precisionDatasetQueriesRepositoryChallengesRetrievalTaskLearningSystemCorpus
2016
- Free-Response ROC Analysis
Zou K, Liu A, Bandos A, Ohno-Machado L, Rockette H. - Free-Response ROC Analysis. 2016, 182-219. DOI: 10.1201/b11031-11.Peer-Reviewed Original Research
2002
Logistic regression and artificial neural network classification models: a methodology review
Dreiseitl S, Ohno-Machado L. Logistic regression and artificial neural network classification models: a methodology review. Journal Of Biomedical Informatics 2002, 35: 352-359. PMID: 12968784, DOI: 10.1016/s1532-0464(03)00034-0.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsMedical data classification tasksNeural network classification modelArtificial neural network (ANN) classification modelData classification tasksNetwork classification modelArtificial neural networkArtificial neural network modelNeural network modelClassification taskNeural networkClassification modelNetwork modelTechnical pointMachineAlgorithmNetworkTaskQuality criteriaModelMethodology reviewSample of papers
2001
A Comparison of Machine Learning Methods for the Diagnosis of Pigmented Skin Lesions
Dreiseitl S, Ohno-Machado L, Kittler H, Vinterbo S, Billhardt H, Binder M. A Comparison of Machine Learning Methods for the Diagnosis of Pigmented Skin Lesions. Journal Of Biomedical Informatics 2001, 34: 28-36. PMID: 11376540, DOI: 10.1006/jbin.2001.1004.Peer-Reviewed Original ResearchConceptsArtificial neural networkDichotomous problemNearest neighborsDifferent classification tasksSpecific classification problemMachine learning methodsMachine-learning methodsClassification taskClassification problemNeural networkLearning methodsDecision tressPigmented skin lesionsVector machineDecision treeTaskNeighborsSVMMachineNetworkBenchmarksCommon neviMethodExcellent resultsGeneration of dynamically configured check lists for intra-operative problems using a set of covering algorithms.
Sawa T, Ohno-Machado L. Generation of dynamically configured check lists for intra-operative problems using a set of covering algorithms. AMIA Annual Symposium Proceedings 2001, 593-7. PMID: 11837218, PMCID: PMC2243696.Peer-Reviewed Original Research