Tag: Artificial Intelligence
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U-M BME to Expand AI Engineering Education with New Master’s Pathway
A new Master’s of Engineering degree in Artificial Intelligence Engineering will prepare biomedical engineers to apply AI and machine learning to real-world challenges in health, medicine, and biotechnology.
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U-M BME Researchers Create an 8D-Model of Cancer Metabolism
In a new study, researchers at the University of Michigan Department of Biomedical Engineering (U-M BME) have harnessed machine learning to successfully predict the metabolic inner workings of nearly 1,000 different cancer cell lines, creating a roadmap that could lead to highly tailored, synergistic combination therapies.
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MIDAS PODS Grant Fuels U-M BME Innovation in Drug Synergy Prediction Using AI
Many computational models work on the principle of “homophily”—assuming that similarly acting drugs will yield the best results. However, this assumption may overlook the complexity of biological systems.
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U-M BME Faculty Pioneer Online Educational Modules on AI Foundations
The development of these online learning modules marks the first step in a broader vision to create a comprehensive educational program focused on AI in BME.
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Michigan Medicine Podcast Features BME’s Anne Draelos
Dr. Anne Draelos highlights how A.I. and Bioinformatics can reveal hidden networks of the brain
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Multimodal AI model may guide personalized treatments for tuberculosis
AI approach helps researchers interpret large biomedical data sets.
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Recent U-M BME Graduate Recognized for Leading Quiescence Research using AI
Quiescence has medical applications
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Paul Jensen Receives NSF Early CAREER Grant to Support Research in AI, Machine Learning
Research to focus on autonomous systems that combine artificial intelligence and automated wet-lab experiments to build mechanistic models of understudied microbes
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Sriram Chandrasekaran Receives Research Scout Grant
Grant to invest in ‘bold science’
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AI Tool Helps Optimize Antibody Medicines
Machine learning points out why antibodies fail to stay on target, binding to molecules that aren’t markers of disease—and suggests better designs.