Publications

The following are peer-reviewed publications of our ongoing research into methods of applied quantitative analysis to guide individual clinical decisions. Our team has made an effort to direct publications toward open-access journals, such that a reader can review the primary literature without the need to manage firewalls. The majority of this work has been funded by grants from the National Institutes of Health.

Device-measured physical activity data for classification of patients with ventricular arrhythmia events: A pilot investigation (PLoS One 2018) 

Applications of Machine Learning in Decision Analysis for Dose Management for Dofetilide (PLoS One 2019)

Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for Prediction of Atrial Fibrillation (JAMA Open 2020)

Multicenter Analysis of Dosing Protocols for Sotalol Initiation (J Cardiovascular Pharmacy Therapy 2020)

Prediction of Incident Myocardial Infarction using Machine Learning Applied to Harmonized Electronic Health Record Data (BMC Med Inform Decision Mak. 2020)

Feasibility of Frailty Assessment Integrated with Cardiac Implantable Electronic Device Clinic Follow-up: A Pilot Investigation (Gerontol Geriatric Med. 2021)

Prediction of Drug-Induced Long QT Syndrome Using Machine Learning Applied to Harmonized Electronic Health Record Data (J Cardiovasc Pharmacol Ther. 2021)

Assessing Prescriber Behavior with a Clinical Decision Support Tool to Prevent Drug-Induced Long QT Syndrome (Appl Clin Inform. 2021)

Trusting Magic: Interpretability of Predictions From Machine Learning Algorithms (Circulation 2021)

Machine Learning Methodologies for Prediction of Rhythm-Control Strategy in Patients Diagnosed With Atrial Fibrillation: Observational, Retrospective, Case-Control Study (JMIR Med Inform. 2021)

Assessment of a Mobile Health iPhone App for Semiautomated Self-management of Chronic Recurrent Medical Conditions Using an N-of-1 Trial Framework: Feasibility Pilot Study (JMIR Form Res. 2022)

Qualitative Evaluation of an Artificial Intelligence-Based Clinical Decision Support System to Guide Rhythm Management of Atrial Fibrillation: Survey Study (JMIR Form Res. 2022)

The Impact of Time Horizon on Classification Accuracy: Application of Machine Learning to Prediction of Incident Coronary Heart Disease (JMIR Cardiology 2022)

Interpretable Machine Learning Prediction of Drug-Induced QT Prolongation: Electronic Health Record Analysis (JMIR 2022)

Evaluation of Quantitative Decision-Making for Rhythm Management of Atrial Fibrillation Using Tabular Q-Learning (JAHA 2023)