Featured Publications
Detecting model misconducts in decentralized healthcare federated learning
Kuo T, Pham A. Detecting model misconducts in decentralized healthcare federated learning. International Journal Of Medical Informatics 2021, 158: 104658. PMID: 34923447, PMCID: PMC10017272, DOI: 10.1016/j.ijmedinf.2021.104658.Peer-Reviewed Original ResearchFederated learningFederated machine learningDetection methodDetection frameworkLearning iterationsMalicious intentLearning methodsMachine learningArtificial intelligenceParameter tuningComputational costCross-institutional collaborationLearningLearning processIterationPerformance detectorsDetectionIncorrect modelFrameworkAlgorithmDatasetDetect misconductIntelligencePlagiarismMethod
2020
EXpectation Propagation LOgistic REgRession on permissioned blockCHAIN (ExplorerChain): decentralized online healthcare/genomics predictive model learning
Kuo T, Gabriel R, Cidambi K, Ohno-Machado L. EXpectation Propagation LOgistic REgRession on permissioned blockCHAIN (ExplorerChain): decentralized online healthcare/genomics predictive model learning. Journal Of The American Medical Informatics Association 2020, 27: 747-756. PMID: 32364235, PMCID: PMC7309256, DOI: 10.1093/jamia/ocaa023.Peer-Reviewed Original ResearchConceptsBlockchain technologyCentral serverServer-based methodBenefits of blockchainData protection policiesCentralized serverArtificial intelligenceModel learningDecentralized approachSmall datasetsBlockchainServerComputation strategySingle pointGeneralizable modelCost of efficiencyGenomic datasetsDatasetDistributed modelTechnologyGenomic dataMultiple institutionsDiscrimination powerIntelligencePotential advantages/disadvantages