2012
A collaborative framework for Distributed Privacy-Preserving Support Vector Machine learning.
Que J, Jiang X, Ohno-Machado L. A collaborative framework for Distributed Privacy-Preserving Support Vector Machine learning. AMIA Annual Symposium Proceedings 2012, 2012: 1350-9. PMID: 23304414, PMCID: PMC3540462.Peer-Reviewed Original ResearchConceptsSupport vector machineVector machinePrivacy-preserving collaborative learningSensitive raw dataPrivacy-preserving mannerEfficient information exchangeDistributed PrivacyLocal repositoryPrivacy concernsCentralized repositoryCollaborative frameworkDecision supportMultiple participantsInformation exchangeRaw dataSVM modelIntermediary resultsMachineCollaborative learningPrivacyPopular toolRepositoryTraditional wayPatient dataServer
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