In the last two decades, the predictive nature of mathematical and computational models has been enhancing the understanding of numerous physiopathological dynamics and the design of therapeutic devices. In silico models are today a regular support not only for the investigative activity of medical doctors and life scientists, but also for advanced clinical practice and the development of healthcare strategies. Still, problems from biomedical research are extremely complex and challenging from the modeling viewpoint. Typically they are characterised by remarkable heterogeneities and multi-scale dynamics, and are imbued with uncertainty. Finally, the huge amount of data currently available requires efficient algorithms that can continuously learn from the generated data, be they clinical or virtual.

In such a framework, the RICAM Special Semester on "Mathematical Methods in Medicine" gathers experts from the modeling, clinical and biological sides to foster the interaction between the two communities, with also the aim to identify relevant challenges for the upcoming years. The semester will account for thematic workshops focusing on cardiovascular diseases and tumor modeling (two of the major causes of deaths in the advanced countries), a workshop on epidemic modeling, and one on the application of ML and AI in the medical field. Finally, a training school will address the crucial issue of Uncertainty Quantification in Biomedical applications.

• Luca Gerardo-Giorda (Johannes Kepler University & RICAM, Austria)
• Argyrios Petras (RICAM, Austria)
• Massimiliano Leoni (RICAM, Austria)