Featured Publications
From Data to Wisdom: Biomedical Knowledge Graphs for Real-World Data Insights
Hänsel K, Dudgeon S, Cheung K, Durant T, Schulz W. From Data to Wisdom: Biomedical Knowledge Graphs for Real-World Data Insights. Journal Of Medical Systems 2023, 47: 65. PMID: 37195430, PMCID: PMC10191934, DOI: 10.1007/s10916-023-01951-2.Commentaries, Editorials and LettersConceptsKnowledge graphReal-world dataGraph modelBiomedical data integrationGraph data modelIntegrated Knowledge GraphBiomedical knowledge graphsElectronic health recordsData integrationData insightsData modelInsight generationBiomedical informationHealth recordsArt researchGraphNovel approachCombination of dataDisease phenotypingInformationPrecision medicine researchHealthcareIntegrationEHRIntriguing opportunityKamino: A Scalable Architecture to Support Medical AI Research Using Large Real World Data
Lin F, Young P, He H, Huang J, Gagne R, Rice D, Price N, Byron W, Hu Y, Felker D, Button W, Meeker D, Hsiao A, Xu H, Torre C, Schulz W. Kamino: A Scalable Architecture to Support Medical AI Research Using Large Real World Data. 2024, 00: 500-504. DOI: 10.1109/ichi61247.2024.00072.Peer-Reviewed Original ResearchElectronic health recordsAI researchNatural language processing tasksElectronic health record dataLanguage processing tasksComputing resource managementLarge-scale data retrievalMedical AI researchLeveraging electronic health recordsStandard data modelKubernetes orchestratorScalable architectureProcessing tasksResource allocation systemsSecurity considerationsAccess managementData retrievalData modelArchitectural solutionsOMOP CDMReal World DataWorld DataHealth recordsOMOPData
2021
Feasibility of capturing real-world data from health information technology systems at multiple centers to assess cardiac ablation device outcomes: A fit-for-purpose informatics analysis report
Jiang G, Dhruva SS, Chen J, Schulz WL, Doshi AA, Noseworthy PA, Zhang S, Yu Y, Young H, Brandt E, Ervin KR, Shah ND, Ross JS, Coplan P, Drozda JP. Feasibility of capturing real-world data from health information technology systems at multiple centers to assess cardiac ablation device outcomes: A fit-for-purpose informatics analysis report. Journal Of The American Medical Informatics Association 2021, 28: 2241-2250. PMID: 34313748, PMCID: PMC8449615, DOI: 10.1093/jamia/ocab117.Peer-Reviewed Original ResearchConceptsReal-world dataHealth information technology systemsInformation technology systemsUnique device identifiersMaturity modelNatural language processing toolsTechnology systemsUnstructured data elementsNatural language processingCommon data modelData quality frameworkLanguage processing toolsComputable phenotypeInformatics approachElectronic health recordsClinical data systemsData modelLanguage processingDevice identifiersStandardized codesData elementsProcessing toolsInformatics technologiesData captureHealth records
2020
The Promise of Big Data and Digital Solutions in Building a Cardiovascular Learning System: Opportunities and Barriers.
Mori M, Khera R, Lin Z, Ross JS, Schulz W, Krumholz HM. The Promise of Big Data and Digital Solutions in Building a Cardiovascular Learning System: Opportunities and Barriers. Methodist DeBakey Cardiovascular Journal 2020, 16: 212-219. PMID: 33133357, PMCID: PMC7587314, DOI: 10.14797/mdcj-16-3-212.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsLearning health systemLearning systemCommon data modelDynamic learning systemAdvanced analyticsBig dataData assetsData modelDigital solutionsCustomer interactionContinuous learningKnowledge generationEffective useConceptual modelAnalyticsSystemGoogleHealth systemLearningComparable scaleModelDataCompanies