MENU Machine Learning for Data-Driven Decisions (MLD3)
We are a part of the AI Lab within the Division of Computer Science and Engineering. We work at the interface of artificial intelligence (AI), machine learning (ML), and healthcare.
| Welcome to the Machine Learning for Data-Driven Decisions Group at the University of Michigan! Our current research portfolio focuses on major public health problems – including infectious diseases, Alzheimer’s disease, and diabetes, respiratory failure, among others. We develop and state-of-the-art AI and machine learning methods to analyze large health datasets. Our work spans several aspects of AI including time-series analysis, reinforcement learning, computer vision, causal inference, and human-computer interaction. We aim to develop the computational methods needed to help organize, process, and transform data into actionable knowledge with the ultimate goal of improving health. You can contact the group by emailing Dr. Jenna Wiens at wiensj@umich.edu. |
- Paper published in IEEE Transactions on Biomedical Engineering. Congratulations Jung Min!
Congratulations to Jung Min Lee on her published paper Shortcoming in the Evaluation of Blood Glucose Forecasting in IEEE Transactions on Biomedical Engineering!
- Paper accepted at ECCV 2024
Congratulations to Sarah Jabbour and Greg Kondas on their recently accepted paper “DEPICT: Diffusion Enabled Permutation Importance for Image Classification Tasks” to ECCV 2024!
- Congratulations, Dr. Shengpu Tang and Dr. Donna Tjandra on your successful PhD thesis defenses!
Shengpu Tang and Donna Tjandra successfully defended their PhDs last week. Congratulations!
- Comment published in Nature Medicine
Congratulations to Meera Krishnamoorthy on her comment “Off-label use of artificial intelligence models in healthcare” published in Nature Medicine!
- Dr. Jenna Wiens on JAMA Podcast with JAMA Editor in Chief Dr. Kirsten Bibbins-Domino
Jenna Wiens, PhD was recently interviewed by JAMA Editor in Chief Kirsten Bibbins-Domino, PhD, MD, MAS, to discuss clinician-AI collaboration for more effective deployment of AI in health. Check it out here!