2011
Using statistical and machine learning to help institutions detect suspicious access to electronic health records
Boxwala A, Kim J, Grillo J, Ohno-Machado L. Using statistical and machine learning to help institutions detect suspicious access to electronic health records. Journal Of The American Medical Informatics Association 2011, 18: 498-505. PMID: 21672912, PMCID: PMC3128412, DOI: 10.1136/amiajnl-2011-000217.Peer-Reviewed Original ResearchConceptsSuspicious accessMachine-learning methodsPrivacy officersMachine learning techniquesVector machine modelAccess logsElectronic health recordsBaseline methodsAccess dataCross-validation setGold standard setSVM modelWhole data setMachine modelBaseline modelOrganizational dataHealth recordsData setsSVM
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 results