Analytics Pillar: Transforming Health Interventions

Health intervention research and implementation is one of the biggest users, as well as inspirations, of cutting-edge data science and AI methods. MIDAS collaborates with campus partners to enable the adoption of cutting-edge analytics and modeling of complex data to boost U-M’s biomedical and healthcare research. Current activities include the following:

Current Activities

Overview: The annual summer academy is open to all U-M researchers and trainees, as well as biomedical scientists from the public and private sectors. We especially welcome faculty members who want to grasp the basic concepts and methods of data science, so that they can start building a data science component in their research, and work more effectively with their data science collaborators. Furthermore, we help like-minded researchers get to know each other through this academy and develop collaboration. Participants are introduced to supervised and unsupervised machine learning, including deep learning; determine which data science/artificial intelligence techniques are appropriate for research application; and hear use cases of data science and AI methods in biomedical research. We also offer follow-up sessions that focus on developing data science components for grant proposals.  

Who Will Benefit: All biomedical scientists who are interested in learning about incorporating data science into their research, but the content is geared towards junior faculty members and those from the public and private sectors. 

Coordinator: Kayvan Najarian (PI, DATA; Associate Director, MIDAS; Professor, Computational Medicine and Bioinformatics) and Ken Reid (Data Scientist, MIDAS)