A machine learning framework to adjust for learning effects in medical device safety evaluation
Koola J, Ramesh K, Mao J, Ahn M, Davis S, Govindarajulu U, Perkins A, Westerman D, Ssemaganda H, Speroff T, Ohno-Machado L, Ramsay C, Sedrakyan A, Resnic F, Matheny M. A machine learning framework to adjust for learning effects in medical device safety evaluation. Journal Of The American Medical Informatics Association 2024, ocae273. PMID: 39471493, DOI: 10.1093/jamia/ocae273.Peer-Reviewed Original ResearchMachine learning frameworkSynthetic datasetsLearning frameworkMachine learningCapacity of MLLearning effectFeature correlationDepartment of Veterans AffairsSynthetic dataData generationAbsence of learning effectsTraditional statistical methodsML methodsSuperior performanceDatasetSafety signal detectionSignal detectionDevice signalsVeterans AffairsTime-varying covariatesLearningMachinePhysician experienceLimitations of traditional statistical methodsMedical device post-market surveillance