activity
20202024
most citedIntegrated multimodal artificial intelligence framework for healthcare applications

367 citations · 457 across the 7 of their papers we have counts for

collaborators

7 papers

math.OC2024

Catastrophe Insurance: An Adaptive Robust Optimization Approach

Dimitris Bertsimas, Cynthia Zeng

The escalating frequency and severity of natural disasters, exacerbated by climate change, underscore the critical role of insurance in facilitating recovery and promoting investme…

cs.LG2023★ 1 cited

Reducing Air Pollution through Machine Learning

Dimitris Bertsimas, Leonard Boussioux, Cynthia Zeng

This paper presents a data-driven approach to mitigate the effects of air pollution from industrial plants on nearby cities by linking operational decisions with weather conditions…

cs.LG2023★ 6 cited

Global Flood Prediction: a Multimodal Machine Learning Approach

Cynthia Zeng, Dimitris Bertsimas

Flooding is one of the most destructive and costly natural disasters, and climate changes would further increase risks globally. This work presents a novel multimodal machine learn…

cs.LG2022★ 6 cited

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…

cs.LG2022★ 367 cited

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…

cs.LG2020★ 65 cited

Hurricane Forecasting: A Novel Multimodal Machine Learning Framework

Léonard Boussioux, Cynthia Zeng, Théo Guénais +1

This paper describes a novel machine learning (ML) framework for tropical cyclone intensity and track forecasting, combining multiple ML techniques and utilizing diverse data sourc…

stat.AP2020★ 12 cited

From predictions to prescriptions: A data-driven response to COVID-19

Dimitris Bertsimas, Léonard Boussioux, Ryan Cory Wright +18

The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a d…