This course will introduce students to the rapidly evolving field of precision medicine and the role of big data analytics in improving patient care, clinical decision making, and population health management. Students will be provided access to the Johns Hopkins Precision Medicine Analytics Platform (PMAP) and learn how the infrastructure is built to support clinical research by integrating data from multiple research and clinical information systems such as the enterprise wide electronic medical record (EMR). The class will provide students access to a de-identified EMR curated dataset of 60k patients with a diagnosis of Asthma. The class will utilize Python and Jupyter notebooks to learn how to analyze EMR data. The PMAP cookbook of Jupyter notebook recipes and Datacamp accounts will be provided for students. After completing the course, students will have an overview of the full lifecycle of a learning health system, from understanding the data elements needed to address their problem, to figuring out the right analysis tools, and finishing with how to take their algorithm and deploy it in the clinical setting as a clinical decision support application.
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