Tsung-Ting Kuo, PhD, FAMIA
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Contact/Administration
Research
Professional Highlights
About
Contact/Administration
Contact Info
Publications Overview
- 71 Publications
- 2,934 Citations
- 4 Yale Co-Authors
Featured Publication
Distributed cross-learning for equitable federated models - privacy-preserving prediction on data from five California hospitals
Honors
- 10 Regional Awards
- 9 National Awards
- 7 International Awards
Education
PhD
National Taiwan University, Institute of Networking and Multimedia (2014)
National Taiwan University, Institute of Networking and Multimedia (2014)
MS
National Chao Tung University, Computer and Information Science (2003)
National Chao Tung University, Computer and Information Science (2003)
BS
National Cheng Kung University, Computer Science and Information Engineering (2001)
National Cheng Kung University, Computer Science and Information Engineering (2001)
Training
Postdoctoral Scholar
University of California San Diego (2019)
University of California San Diego (2019)
Contact Info
Publications Overview
- 71 Publications
- 2,934 Citations
- 4 Yale Co-Authors
Featured Publication
Distributed cross-learning for equitable federated models - privacy-preserving prediction on data from five California hospitals
Honors
- 10 Regional Awards
- 9 National Awards
- 7 International Awards
Education
PhD
National Taiwan University, Institute of Networking and Multimedia (2014)
National Taiwan University, Institute of Networking and Multimedia (2014)
MS
National Chao Tung University, Computer and Information Science (2003)
National Chao Tung University, Computer and Information Science (2003)
BS
National Cheng Kung University, Computer Science and Information Engineering (2001)
National Cheng Kung University, Computer Science and Information Engineering (2001)
Training
Postdoctoral Scholar
University of California San Diego (2019)
University of California San Diego (2019)
Contact Info
About
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We focus on designing and implementing advanced methods on decentralized blockchain networks to improve the security and robustness of data sharing/analysis frameworks.
Titles
Associate Professor of Biomedical Informatics and Data Science and Surgery
Biography
Kuo is an Associate Professor of Biomedical Informatics and Data Science (BIDS) and of Surgery at Yale School of Medicine, and a Fellow of American Medical Informatics Association (FAMIA). He earned his PhD from National Taiwan University (NTU) in the Institute of Networking and Multimedia.
Kuo was previously assistant professor of medicine at University of California San Diego (UCSD) Health's Department of Biomedical Informatics (DBMI). Prior to becoming a faculty member, he was a Postdoctoral Scholar at UCSD DBMI and received the UCSD Chancellor’s Outstanding Postdoctoral Scholar Award. He was a major contributor towards the UCSD DBMI team winning the Office of the National Coordinator for Health Information Technology (ONC) healthcare blockchain challenge, and also the NTU team winning the Association for Computing Machinery (ACM) Knowledge Discovery and Data Mining (KDD) Cup competition four times.
Kuo was awarded NIH R01 Research Project Grants, K99/R00 Pathway to Independence Award with an Administrative Supplement, R13 Support for Conferences and Scientific Meetings Grant, as well as UCSD Academic Senate Health Science Research Grants, for blockchain-based and predictive studies in biomedical, healthcare and genomic fields. His research focuses on distributed private modeling, blockchain, artificial intelligence, and natural language processing.
Last Updated on November 05, 2025.
Appointments
Biomedical Informatics & Data Science
Associate Professor on TermPrimarySurgery
Associate Professor on TermSecondary
Other Departments & Organizations
Education & Training
- Postdoctoral Scholar
- University of California San Diego (2019)
- PhD
- National Taiwan University, Institute of Networking and Multimedia (2014)
- MS
- National Chao Tung University, Computer and Information Science (2003)
- BS
- National Cheng Kung University, Computer Science and Information Engineering (2001)
Research
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Overview
Our research focused on biomedical blockchain that can advance research by data sharing. Currently, state-of-the-art data sharing and analysis frameworks across multiple healthcare systems are mostly still centralized. This centralization carries several risks at the central server, such as single-point-of-failure and data mutability. To improve the security and robustness of data sharing/analysis frameworks, we focus on designing and implementing advanced methods on decentralized blockchain networks. Blockchain is a distributed ledger/database technology adopted by Bitcoin and other cryptocurrencies. We aim at developing novel approaches that can enhance the security and robustness of data sharing/analysis from multiple medical institutions through a distributed system.
Medical Research Interests
Artificial Intelligence; Blockchain; Genetic Privacy; Natural Language Processing; Privacy
ORCID
0000-0002-8728-4477
Research at a Glance
Publications Timeline
A big-picture view of Tsung-Ting Kuo's research output by year.
Research Interests
Research topics Tsung-Ting Kuo is interested in exploring.
Yale Co-Authors
Frequent collaborators of Tsung-Ting Kuo's published research.
71Publications
2,934Citations
Blockchain
Privacy
Natural Language Processing
Lucila Ohno-Machado, MD, MBA, PhD
Jihoon Kim, PhD
Hua Xu, PhD
Daniella Meeker, PhD
Publications
Featured Publications
Distributed cross-learning for equitable federated models - privacy-preserving prediction on data from five California hospitals
Kuo T, Gabriel R, Koola J, Schooley R, Ohno-Machado L. Distributed cross-learning for equitable federated models - privacy-preserving prediction on data from five California hospitals. Nature Communications 2025, 16: 1371. PMID: 39910076, PMCID: PMC11799213, DOI: 10.1038/s41467-025-56510-9.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsHeart disease dataParts of informationLearning counterpartsCentralized solutionVertical scenariosPatient privacyPredictive analyticsFederated modelSynchronization timePrivacyUC San DiegoPatient-level recordsDisease dataPatient dataPrediction modelPatient careHealthcare centersUniversity of CaliforniaCalifornia hospitalsHealthcare systemQuality improvementPatient records
2025
False-positive tolerant model misconduct mitigation in distributed federated learning on electronic health record data across clinical institutions
Edelson M, Pham A, Kuo T. False-positive tolerant model misconduct mitigation in distributed federated learning on electronic health record data across clinical institutions. Scientific Reports 2025, 15: 23310. PMID: 40603924, PMCID: PMC12223104, DOI: 10.1038/s41598-025-04069-2.Peer-Reviewed Original ResearchMeSH Keywords and ConceptsConceptsLearning scenariosFederated learning scenarioCollaborative machine learningDecentralized blockchain networkFederated learning processMachine learning algorithmsFederated LearningBlockchain networkBlockchain characteristicsLearning algorithmsSecurity risksMachine learningCharacteristics of transparencyExcessive false alarmsElectronic health record dataFalse alarmsModel integrationCross-institutionalLearning processNetworkRobust approachPredictive health modelLearningCollaborative healthcareScenariosSupporting Patients in Managing Electronic Health Records and Biospecimens Consent for Research: Insights from a Mixed-Methods Usability Evaluation of the iAGREE Portal
Di Hu, Xi Lu, Yunan Chen, Michelle Keller, An T. Nguyen, Vu Le, Tsung-Ting Kuo, Lucila Ohno-Machado, and Kai Zheng, “Supporting Patients in Managing Electronic Health Records and Biospecimens Consent for Research: Insights from a Mixed-Methods Usability Evaluation of the iAGREE Portal.” AMIA Annual Symposium, 2025Peer-Reviewed Original Research
2024
Predicting positive Clostridioides difficile test results using large-scale longitudinal data of demographics and medication history
Pham A, El-Kareh R, Myers F, Ohno-Machado L, Kuo T. Predicting positive Clostridioides difficile test results using large-scale longitudinal data of demographics and medication history. Heliyon 2024, 11: e41350. PMID: 39958729, PMCID: PMC11825254, DOI: 10.1016/j.heliyon.2024.e41350.Peer-Reviewed Original ResearchAltmetricConceptsArea under the receiver operating characteristic curveMedical historyClostridioides difficile infectionMonths of medical historyPatient's chancesData of demographicsReceiver operating characteristic curveLogistic regression modelsHealth patientsModerate sample sizesPregnant womenHealthcare institutionsClostridioides difficileAntibiotic useOdds ratioNegative casesLarge-scale longitudinal dataFinancial incentivesPositive testLogistic regressionPatientsIncreased susceptibilityCharacteristic curveRegression modelsSignificant covariatesDistributed, immutable, and transparent biomedical limited data set request management on multi-capacity network
Yu Y, Edelson M, Pham A, Pekar J, Johnson B, Post K, Kuo T. Distributed, immutable, and transparent biomedical limited data set request management on multi-capacity network. Journal Of The American Medical Informatics Association 2024, 32: 296-307. PMID: 39569448, PMCID: PMC11756586, DOI: 10.1093/jamia/ocae288.Peer-Reviewed Original ResearchCitationsAltmetricConceptsBlockchain-based systemSmart contractsMedical data managementData access processReal-world scenariosData access historyRuntime metricsAccess transparencyAudit logMetadata InitiativeNetwork speedPerformance gainsSharing requestsAccess historyRequest managementHardware specificationsComputing capacityAverage runtimeData managementSharing processSynthetic dataRequest timeQueryAudit trailData linksWebQuorumChain: A web framework for quorum-based health care model learning
Shao X, Pham A, Kuo T. WebQuorumChain: A web framework for quorum-based health care model learning. Informatics In Medicine Unlocked 2024, 50: 101590. PMID: 39483487, PMCID: PMC11526443, DOI: 10.1016/j.imu.2024.101590.Peer-Reviewed Original ResearchCitationsConceptsExecution timeBack-endDecentralized federated learningDecentralized machine learningFederated learning networkFront-endAverage execution timeBack-end layerBack-end functionsWeb-based systemData-Driven DiscoveryFederated LearningPrivacy-preservingData privacyPrivacy concernsRuntime efficiencyCollaborative machinesWeb frameworkModel learningSecurity promisesSystem overheadsLow-level processingLearning networkMachine learningVisualization toolsSecure Federated Learning Integrated Statistical Modeling for Healthcare Data
Jiang X, Kim J, Kuo T, Ohno-Machado L. Secure Federated Learning Integrated Statistical Modeling for Healthcare Data. 2024, 313-324. DOI: 10.1201/9781003185284-24.Peer-Reviewed Original ResearchDistributed management of patient data-sharing informed consents for clinical research
Pham A, Edelson M, Nouri A, Kuo T. Distributed management of patient data-sharing informed consents for clinical research. Computers In Biology And Medicine 2024, 180: 108956. PMID: 39121682, PMCID: PMC11380755, DOI: 10.1016/j.compbiomed.2024.108956.Peer-Reviewed Original ResearchCitationsConceptsBenefits of immutabilityBlockchain-based infrastructureMulti-site scenarioResearch Data AccessNode parallelismOn-chainNetwork nodesData accessAudit trailPatient privacyDistribution managementConsent mechanismsData categoriesNodesEfficient wayNetworkAutomated channelAccuracyQueryPrivacyImmutabilityOrchestrationConsent protocolDataExhaustive listBiomedical blockchain with practical implementations and quantitative evaluations: a systematic review
Lacson R, Yu Y, Kuo T, Ohno-Machado L. Biomedical blockchain with practical implementations and quantitative evaluations: a systematic review. Journal Of The American Medical Informatics Association 2024, 31: 1423-1435. PMID: 38726710, PMCID: PMC11105130, DOI: 10.1093/jamia/ocae084.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsElectronic health recordsSystematic reviewData sharingMedical data sharingSpeed metricsPreferred Reporting ItemsCertificate storageDecentralized InternetNetwork permissionsBlockchain platformBlockchain applicationsEvaluation metricsBiomedical domainBlockchainBiomedical data managementHealth recordsData managementData storageReporting ItemsHealth sectorQuantitative metricsMedical facilitiesMetricsTrial managementClinical trial managementEarly prediction of long hospital stay for Intensive Care units readmission patients using medication information
Zhang M, Kuo T. Early prediction of long hospital stay for Intensive Care units readmission patients using medication information. Computers In Biology And Medicine 2024, 174: 108451. PMID: 38603899, PMCID: PMC11385457, DOI: 10.1016/j.compbiomed.2024.108451.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsIntensive care unitProlonged ICU LOSAverage doseICU LOSLonger hospital stayReceiver operating characteristic curveLogistic regressionPredicting intensive care unitMedical informationExpected calibration errorSummed dosePatient ageHospital staySupport vector machineCare unitMIMIC-IV databasePatient complicationsCharacteristic curveMedicationRandom forestDosePatient recordsAdmissionReadmission patients
Academic Achievements & Community Involvement
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Honors
honor Elected Fellow of American Medical Informatics Association (FAMIA)
01/01/2025National AwardAMIAhonor Excellent Editorial Board Member Award
01/01/2024National AwardJAMIADetailsUnited Stateshonor Academic Senate Health Science Travel Award
01/01/2023Regional AwardUniversity of California San DiegoDetailsUnited Stateshonor Academic Senate Health Science Travel Award
01/01/2021Regional AwardUniversity of California San DiegoDetailsUnited Stateshonor Faculty of the Year
01/01/2020Regional AwardUniversity of California San Diego Biomedical InformaticsDetailsUnited States
News & Links
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News
- November 11, 2025
Tsung-Ting Kuo Inducted into 2026 AMIA Fellowship
- September 17, 2025Source: NIH Reporter
Yale BIDS Awarded $2.7 Million NIH Grant to Develop AI Explainability Tools for Clinical Decision-Making
- February 05, 2025Source: Nature Communications
Distributed Cross-Learning for Equitable Federated Models - Privacy-Preserving Prediction on Data from Five California Hospitals
- January 29, 2025
Advancing Privacy in Biomedical Data Sharing: Yale BIDS Leading the Charge
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