Taking a closer look at survival modeling with ECGs
The Cava laboratory is a research group interested in improving the trustworthiness of artificial intelligence (AI) models deployed in healthcare settings. We study algorithmic notions of interpretability, fairness, accuracy, and robustness in medical applications of AI.
The lab is part of the Computational Health Informatics Program at Boston Children’s Hospital, affiliated with Harvard Medical School.
Recent Papers
Iterative Learning of Computable Phenotypes for Treatment Resistant Hypertension using Large Language Models
Machine Learning for Healthcare (MLHC)
Call for Action: towards the next generation of symbolic regression benchmark
Proceedings of the Genetic and Evolutionary Computation Conference Companion
Recent Posts
Relaxing the definition of equivalent mathematical expressions to get simpler and more interpretable models
About our recent HUMIES award-winning algorithm for clinical prediction models