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Precision Care Medicine is a two-semester project-based learning course. Projects will use methods of machine learning and mechanistic and statistical modeling to develop novel data-driven solutions to important health care problems that arise in various medical disciplines including critical care, neurology, immunology, cardiovascular care, and more. The scope of such problems is vast, and few have been approached before. Examples include data- and modeling-driven approaches to: optimal determination of when it is safe to discharge a patient from an ICU; early prediction of pending changes in the clinical state of patients in an ICU or OR; data-driven optimal selection of patient interventions and therapies; and many more. In the first semester, students will assemble into teams of 5-6, and will work with their project mentors (clinical faculty in Johns Hopkins Medicine; Drs. Greenstein and Taylor) to develop a project work plan. In the remainder of the course, they will apply engineering approaches to solve the important health care problems in their projects. Class time will include both clinical and technical lectures and tutorials covering the physiology, medicine, and engineering principles relevant to each project as well as advisory meetings where faculty are available to provide project-specific guidance and assist students with challenges. HIPAA regulations, IRB protocols, and use of human subjects data will be covered. Each team will present project updates to the entire class at regular intervals so that every student becomes familiar with each project. Teams will be charged with designing and validating their models and preparing results for publication by the end of the second semester. Auditing is not permitted. There is a required one-hour weekly meeting between the student project team and project team PI.