367 citations · 375 across the 5 of their papers we have counts for
5 papers
M3H: Multimodal Multitask Machine Learning for Healthcare
Dimitris Bertsimas, Yu Ma
Developing an integrated many-to-many framework leveraging multimodal data for multiple tasks is crucial to unifying healthcare applications ranging from diagnoses to operations. I…
Towards Stable Machine Learning Model Retraining via Slowly Varying Sequences
Dimitris Bertsimas, Vassilis Digalakis, Yu Ma +1
We consider the problem of retraining machine learning (ML) models when new batches of data become available. Existing approaches greedily optimize for predictive power independent…
Robust Regression over Averaged Uncertainty
Dimitris Bertsimas, Yu Ma
We propose a new formulation of robust regression by integrating all realizations of the uncertainty set and taking an averaged approach to obtain the optimal solution for the ordi…
TabText: Language-Based Representations of Tabular Health Data for Predictive Modelling
Kimberly Villalobos Carballo, Liangyuan Na, Yu Ma +4
Tabular medical records remain the most readily available data format for applying machine learning in healthcare. However, traditional data preprocessing ignores valuable contextu…
Integrated multimodal artificial intelligence framework for healthcare applications
Luis R. Soenksen, Yu Ma, Cynthia Zeng +7
Artificial intelligence (AI) systems hold great promise to improve healthcare over the next decades. Specifically, AI systems leveraging multiple data sources and input modalities…