The Medical Machine Learning Lab
We bridge the gap between state-of-the-art machine learning and medical practice to improve personalized patient care.
Research
The Medical Machine Learning Lab, situated at the Institute of Translational Psychiatry, develops Machine Learning solutions in all areas of medicine - from tools improving research to prototypes of clinical decision support systems. With the use of deep learning, causal inference, control theory, time series analysis, graph analytics, and many more, we develop cutting-edge machine learning solutions, with the goal of improving healthcare and medical research.
Machine Learning Infrastructure
PHOTONAI, a high-level API for Machine Learning, streamlines the development of advanced models tailored for clinical research. It automates tasks like training and hyperparameter optimization, ensuring unbiased performance estimates. PHOTONAI supports the integration of diverse data domains, enhancing predictive performance by combining sources of varying dimensions. The platform includes an online model evaluation platform and a public model repository, facilitating automatic testing across different sites. Adopted by the ENIGMA consortium, it evaluates Brain Age machine learning models.
Evaluation and Certification
The Medical AI Quality Assessment and Compliance Hub focuses on enhancing the quality and reliability of healthcare Machine Learning applications. Their mission is to ensure clinical excellence, replicability, and adherence to ethical and legal standards. The platform provides a space for rigorous evaluation and improvement of medical AI systems, building trust among healthcare professionals and patients. Services are tailored to address challenges in medical AI, leveraging extensive experience in Machine Learning best practices. Collaboration with the Faculty of Law incorporates evolving healthcare regulations on AI applications in medical settings. For more details, refer to the provided links.
About us
The Medical Machine Learning Lab (MMLL), situated at the Institute of Translational Psychiatry, is a leading research group in medical Machine Learning (ML) led by Tim Hahn at the University of Münster. We develop cutting-edge ML, with the goal of improving healthcare and medical research, using deep learning, causal inference, control theory, time series analysis, graph ML, and many more. Our focus is on providing ML software infrastructure for large-scale research projects, ensuring best-practice ML via software, consulting and certification.