<p>Lecture, four hours; discussion, two hours. Requisite: course 200 or equivalent. Development and application of algorithmic approaches to problems in biomedicine, with focus on formulating interdisciplinary problems as computational problems and then solving these problems using algorithmic techniques. Design, analysis, optimization, and implementation of algorithms. Topics include string algorithms in genomics and scalable machine learning algorithms applied to medical data. Satisfies capstone requirement. Students present their results. Letter grading.</p>

Data Science in Biomedicine

The school is a groundbreaking community of problem solvers, caregivers, innovators, and life-long learners with a noble mission: to heal humankind by delivering leading-edge research, education, patient care, and community engagement.

David Geffen School of Medicine

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The department's primary goal is to build and implement the mathematical models that are crucial for the advancement of modern biomedical sciences.

Computational Medicine

DS BMED 219 - Data Science Algorithms in Biomedicine

Data Science Algorithms in Biomedicine

Obtain knowledge of biomedical datasets including genomics, electronic health records and medical images.

Obtain foundational knowledge and technical skill in data science.

Learn how to read papers on algorithms in biomedicine.

General Catalog

Data Science Algorithms in Biomedicine

DS BMED 219

4 units