Open AI in health
Making AI research reproducible and open
This Helmholtz AI group works at the intersection of open science, AI and health research. Our research focuses on how (health) AI research is conducted, raise awareness for issues, as well as provide solutions. We use best practices from the medical field and use them to improve AI research and we develop AI methods to improve health research. AI applied to health research offers special challenges (e.g. privacy, ethics, trust), which we take into account throughout all our work.
We value collaboration, transparency, and diversity.
- Supervised learning
- Model-based trees and random forests for personalized medicine
- Regression
- Democratizing artificial intelligence and machine learning: access, support, trust and reusability
Data protection note
Research lines
- Open and reproducible research in AI and health research
- Model-based trees and random forests
- Personalized medicine / personalized treatment effect estimation
- Open source software
Team
- Heidi Seibold, group leader
- Mohammad Mirkazemi, research software engineer
- Lea Schulz-Vanheyden, master student
Links
Community contributions
- German Reproducibility Network
- LMU Open Science Center and LMU Open Science Initiative in Medicine
- Open scholarship expert group, Knowledge Exchange
- Working group Scientific Practice, Schwerpunktinitiative „Digitale Information“, Allianz der deutschen Wissenschaftsorganisationen
- Journal of Statistical Software (replication editor)
- deRSE: association of the German research software engineers
- Helmholtz UQ
- OpenML
- The Turing Way