Using Data Science to Personalize Depression Care

How can data science contribute to better healthcare? This summer, five young researchers are exploring exactly that question as part of DSSGx Munich 2026, supported by the MCML.

How can data science contribute to better healthcare? This summer, five young researchers are exploring exactly that question as part of DSSGx Munich 2026, supported by the MCML.

Data Science for Social Good (DSSG) brings together talented young data scientists from around the world to apply their skills to real-world challenges with societal impact. Since 2023, a local branch of the international initiative has been hosted in Munich by LMU Munich’s Department of Statistics together with MCML. From August to October, the DSSGx Munich fellows work full-time in interdisciplinary teams, combining different academic backgrounds, perspectives, and data science methods.

Data Science for More Personalized Depression Care

This year’s project addresses an important challenge in healthcare: How can Collaborative Care for Depression in German primary care be implemented as effectively as possible for different patients?

Collaborative Care combines different elements of depression treatment and brings together professionals from different areas of healthcare. Yet not every patient necessarily benefits from the same combination of interventions.

Using data from LMU University Hospital, the DSSGx team is investigating how individual treatment components relate to patient outcomes and which combinations may work particularly well for specific patient profiles.

The long-term goal is to contribute towards an intuitive, patient-centered prediction tool, developed with input from general practitioners, that could provide data-driven decision support. Such an approach could help use healthcare resources more effectively while supporting better patient outcomes.

Different Perspectives, One Shared Challenge

From ecological data science and public policy to computer vision, engineering and applied machine learning, the five fellows Loiruck Godwin, Alexander Richard, Boaz Kafuti, Xiaohan Wu and Amina Dzafic bring very different perspectives to the project. Over nine intensive weeks in Munich, the team will explore what data can tell us about more personalized and effective depression care while gaining first-hand experience of what it means to translate data science into social impact.

We are excited to follow their journey and see where their different perspectives take them.

**Learn more about DSSGx Munich and the 2026 program:
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