European Conference on Mathematical and Theoretical Biology (ECMTB 2026)

Integrating machine learning into mathematical oncology

Not scheduled

20m

University of Graz

Minisymposium Mathematical Oncology Integrating machine learning into mathematical oncology

Speakers

Sébastien Benzekry Alvaro Kohn Luque Daniel Camacho-Gomez (Moffitt Cancer Center) Lucas Zimmer (1AI for Image-Guided Diagnosis and Therapy, Technical University of Munich, Germany)

Description

Cancer is a complex multiscale disease characterized by heterogeneous cellular behaviors, nonlinear dynamics, and interactions across scales. Computational models provide a formal framework to study cancer progression, predict treatment response, and support translational research. However, significant challenges remain due to spatial and temporal scales, nonlinear behavior, and the high-dimensional, heterogeneous data that are difficult to integrate into mechanistic frameworks. Machine learning approaches easily integrate multi-modal data across diverse spatial and temporal scales to make classifications and predictions but often this comes at the cost of interpretability that is standard in mathematical oncology. This minisymposium aims to bring together researchers to discuss recent advances in integrating machine learning with mechanistic models for cancer research in (1) hybrid approaches combining mechanistic models and machine learning; (2) machine learning methods for calibration and adaptation of mechanistic models; (3) mechanistic learning approaches to improve interpretability, robustness, and generalization; and (4) machine learning models for knowledge discovery, pattern extraction, and guidance of new mechanistic models. Applications span in vitro, in vivo, and patient-specific digital twins for personalized cancer progression prediction, and treatment planning.

Bibliography

@article{rockne_future_2026,
title = {The future of mathematical oncology in the age of {AI}},
volume = {12},
issn = {2056-7189},
url = {https://www.nature.com/articles/s41540-026-00656-9},
doi = {10.1038/s41540-026-00656-9},
language = {en},
number = {1},
urldate = {2026-05-19},
journal = {npj Systems Biology and Applications},
author = {Rockne, Russell C. and Andersen, Morten and Anderson, Alexander R. A. and Basanta, David and Bentivegna, Angela and Benzekry, Sebastien and Branciamore, Sergio and Brüningk, Sarah C. and Conte, Martina and Farahpour, Farnoush and Karolak, Aleksandra and Köhn-Luque, Alvaro and Lorenzo, Guillermo and Manookian, Babgen and Rodin, Andrei S. and Schmalenstroer, Lara and Soler, Juan and Tomasetti, Cristian and Urbaniak, Konstancja},
month = jan,
year = {2026},
pages = {22},
}