My research focuses on the application of statistical and machine learning approaches for the assessment of complex predictors and interactions in precision cardiovascular medicine and exposome-wide analysis. More details and several slides of recent talks and presentations are available here
Recent Publications
Prasad S, Murphy SA, Morrow DA, Scirica BS, Sabatine MS, Berg DD, Bellavia A. Application of Machine Learning and Deep Learning Approaches for Prediction Modeling with Time-To-Event Outcomes in Clinical Epidemiology. Methods Comparison and Practical Considerations for Generalizability and Interpretability. Annals of Epidemiology
Thiesmeier R, Haller PM, Patel SM, Morrow DA, Murphy SA, O’Donoghue ML, Sabatine MS, Scirica BS, Bhatt DL, Orsini N, Bellavia A. Statistical approaches for systematically missing covariates in individual participant data meta-analysis: insights and applications using 5 large cardiovascular trials. American Journal of Epidemiology
Ponzano M, Rotem RS, Bellavia A. Complex methods for complex data: key considerations for interpretable and actionable results in exposome research. European Journal of Epidemiology
Discacciati A, Palazzolo MG, Park JG, Melloni, GEM, Murphy SA, Bellavia A. Estimating and Presenting Non-Linear Associations with Restricted Cubic Splines. International Journal of Epidemiology
Bellavia A, Murphy SA. Confounders, effect modifiers, mediators. Dealing with ‘third variables’ in cardiovascular epidemiology. Circulation
Full list of publications: link
Statistical Methods for Environmental Mixtures: A Primer in Environmental Epidemiology. Springer, 2024
Accompanying R material available here