PfeiferLab’s interdisciplinary research in medical informatics focuses on solving biomedical problems by developing and extending state-of-the-art machine learning and AI methods. Our aim is to help the prevention and/or treatment of, for instance, SARS-CoV-2, HIV, HCV, or influenza infections, as well as malaria, cancer and other diseases based on clinical, genomic and epigenomic data. We also develop privacy-preserving machine learning methods that keep the data private while at the same time enabling high prediction performance. Last but not least we do actual translational software development and deployment to hospitals.
Our expertise at the intersection of computer science and medicine contributes to facilitating crucial connections to:
For more details, see our publications, research projects and software.
