AI Applctn in Systems Medicine

3 Credits · Level: Graduate, Undergraduate

This comprehensive 3-credit course delves into the interdisciplinary field of Systems Medicine and explores its integration with Artificial Intelligence (AI) in the context of healthcare. Students will learn how AI techniques, including machine learning, deep learning, and data analytics, can be leveraged to analyze complex biological systems, decipher disease mechanisms, and personalize medical treatments. The course covers foundational concepts in systems medicine, including omics technologies, network biology, and personalized medicine, while examining how AI methodologies can enhance our understanding of health and disease. Throughout the course, students will explore the interdisciplinary intersection of Systems Medicine and AI within healthcare. Through engaging lectures, interactive discussions, illuminating case studies, and hands-on projects, they will delve into AI techniques such as machine learning, deep learning, and data analytics. These techniques will be applied to analyze complex biological systems and personalize medical treatments, with a particular focus on integrating real-world data extracted from Electronic Health Record (EHR) systems. By the end of the course, students will have gained practical skills in AI-enabled systems medicine and developed the ability to apply these techniques to real-world biomedical problems, leveraging EHR data to enhance their understanding and impact in healthcare.