What does generative AI mean for health care? We asked the experts

We have been featured in an article on large language models in healthcare!

Sarah Jabbour selected for CSE HACKS Spirit Award

Congratulations to Sarah Jabbour for receiving the HACKS Spirit Award!

PhD student perspectives in CSE: Sarah Jabbour

Sarah Jabbour • 2023

Jenna Wiens receives U-M Sarah Goddard Power Award for outstanding research and advocacy for women in academia

Congratulations to Jenna Wiens for receiving the Sarah Goddard Power Award!

Diversity and inclusiveness are an essential part of the pursuit of AI at CSE

We have been featured in an article on diversity and inclusion from the Michigan AI Lab!

“It’s a supportive and collaborative environment” — making connections as a PhD student in and outside the classroom

Sarah Jabbour shares the story of her journey into computer science and graduate school!

2022 CSE Graduate Student Honors Competition highlights outstanding research

Congratulations to Shengpu Tang for winning second place at the University of Michigan CSE Honors Competition!

Decisive Differences in Healthcare AI

Trenton Chang discusses his research in an interview with Rackham!

Disparate Censorship & Undertesting: A Source of Label Bias in Clinical Machine Learning

Trenton Chang • MLHC 2022

Reinforcement Learning with Set-Valued Policies • PathCheck Global Health Innovators Seminar

Shengpu Tang • August 12, 2021

Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare Settings | MLHC 2021

Shengpu Tang • MLHC 2021

Mind the Performance Gap: Examining Dataset Shift During Prospective Validation | MLHC 2021

Erkin Otles and Jeeheh Oh • MLHC 2021

From Diagnosis to Treatment – Augmenting Clinical Decision Making with Artificial Intelligence • Temerty Speaker Series

Dr. Jenna Wiens • May 11, 2021

Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts

Sarah Jabbour • MLHC 2020

Deep Reinforcement Learning for Closed-Loop Blood Glucose Control

Ian Fox • MLHC 2020

Clinician-in-the-loop RL with Set-Valued Policies | ICML 2020

Shengpu Tang | More details on icml.cc

Deep Residual Time-Series Forecasting: Application to Blood Glucose Prediction

Presented at 2020 KDH Blood Glucose Level Prediction Challenge

MCURES | CRA Virtual Conference 2020

a COVID predictive model developed specifically for the Michigan Medicine population: the Michigan COVID-19 Utilization and Risk Evaluation System, or MCURES. 

Friday Night AI: AI and COVID-19 | 2020

Erkin Otles speaks about M-CURES, a machine learning model developed by people from our lab. M-CURES can help clinicians tell which COVID-19 patients are most likely to deteriorate.

Stanford Medicine Big Data | Precision Health 2018

Jenna Wiens, University of Michigan

How can machine-learning impact healthcare? | 2018 UM-CSE research highlight

Prof. Jenna Wiens uses machine learning to make sense of the immense amount of patient data generated by modern hospitals. This can help alleviate physician shortages, physician burnout, and the prevalence of medical errors.

AI for Health: Augmenting Clinical Care | Michigan AI Symposium 2018