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Overview

About This Course​

CACoM (Clinical Applications of Computational Medicine) is a project-based course at the Technical University of Munich, where students work in small teams to design, execute, and present data-driven research projects at the intersection of computation and clinical medicine.

CACoM's Guiding Idea

At its core, CACoM is guided by a simple but powerful idea:

Improving human health.

If your project contributes to that goal — even in a small, indirect, or exploratory way — you are very likely moving in the right direction.

In addition to the project work, the course includes lectures by internal instructors and guest talks from clinicians, researchers, and industry partners. These sessions introduce students to diverse real-world applications of computational medicine and illustrate how data science, statistics, and engineering are transforming modern healthcare.

By the end of the course, you will have learned to formulate a research question, identify and analyze relevant data, apply appropriate computational methods, and communicate findings effectively to both technical and medical audiences.

A(n) (Im)Modest Expectation

By the end of the semester, we hold an immodest expectation — that many of you will look back and consider CACoM the best course you’ve taken at TUM.
(That's not just wishful thinking — it's based on feedback from previous cohorts in our course evaluations. Just see here and here)

Start Here

If you're new, begin with the Schedule and then check the Project Proposal Guide.

Course Format​

  • Lectures — covering clinical and computational foundations.
  • Student projects — 1–7 students per team, mentored by staff.
  • Guest talks — from clinicians, researchers, and industry experts.
  • Final presentations — 1-minute video + poster session.

Learning Outcomes​

By completing CACoM, you will:

  • Understand how computational methods are applied in modern medicine.
  • Gain experience managing small, interdisciplinary research projects.
  • Develop presentation and scientific communication skills.
  • Appreciate how computation can meaningfully contribute to improving human health.

Affiliation​