Relaxing the definition of equivalent mathematical expressions to get more simpler and interpretable models
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
Electrocardiogram-based deep learning to predict mortality in paediatric and adult congenital heart disease
European Heart Journal
Deep Learning-Based Electrocardiogram Analysis Predicts Biventricular Dysfunction and Dilation in Congenital Heart Disease
Journal of the American College of Cardiology
Recent Posts
About our recent HUMIES award-winning algorithm for clinical prediction models
A new perspective on how this social theory relates to fair machine learning.