The Cava laboratory is a research group in the Computational Health Informatics Program at Boston Children’s Hospital and Harvard Medical School.

We are interested in improving the interpretability and fairness of predictive models deployed in healthcare settings. We create and study algorithms that can embed these notions when working with health data.

Join the Team! If you’re looking to do research in the areas of machine learning, interpretability, fairness, and health informatics, see the opportunities here.

Recent Papers

Intersectional consequences for marginal fairness in prediction models of emergency admissions
Elle Lett, Shakiba Shahbandegan, Yuval Barak-Corren, Andrew Fine, William G La Cava (2024)
Preprint
Electrocardiogram-based deep learning to predict mortality in paediatric and adult congenital heart disease
Joshua Mayourian, Amr El-Bokl, Platon Lukyanenko, William G La Cava, Tal Geva, Anne Marie Valente, John K Triedman, Sunil J Ghelani (2024)
European Heart Journal
Deep Learning-Based Electrocardiogram Analysis Predicts Biventricular Dysfunction and Dilation in Congenital Heart Disease
Joshua Mayourian, Addison Gearhart, William G. La Cava, Akhil Vaid, Girish N. Nadkarni, John K. Triedman, Andrew J. Powell, Rachel M. Wald, Anne Marie Valente, Tal Geva, Son Q. Duong, Sunil J. Ghelani (2024)
Journal of the American College of Cardiology

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