Program Information

Program Description

The Master of Science in Biomedical Data Science and AI (MDSAI) program at the Icahn School of Medicine at Mount Sinai integrates training and education in various aspects of biomedical sciences with machine learning, computer systems, and big data analysis, as well as access to large electronic medical record- linked biomedical repositories. Housed within the Graduate School of Biomedical Sciences, our program offers a unique opportunity for students with a strong quantitative background to hone the skills necessary to enrich—and ultimately to lead—the biomedical workforce of tomorrow.

Our curriculum provides rigorous training in both biomedical sciences, through an intensive semester- long core course, and quantitative data analysis, through innovative required and elective courses. Electives can include choices in our exciting biomedical innovation and entrepreneurship curriculum. Our goal is to motivate students to devise innovative approaches to challenging biomedical problems in order to revolutionize personalized medicine and healthcare.

Learning Objectives for the MDSAI Program Graduates of the MDSAI program will be able to:

Apply computational, mathematical, and statistical reasoning to analyze and interpret complex biomedical data.
Integrate machine learning and computer systems concepts with biomedical science to address challenges in health and disease.
Conduct advanced analyses using big data tools and visualization techniques to derive meaningful insights from large-scale biomedical datasets.
Leverage electronic health records and other large biomedical data repositories to develop and apply data-driven approaches for personalized medicine.
Design and implement innovative analytic tools and methodologies tailored to biomedical research and clinical applications.
Collaborate effectively across disciplines to contribute to the development of next-generation solutions in medicine and healthcare.
Communicate complex quantitative findings clearly and effectively to both technical and non-technical audiences in biomedical and healthcare settings.