Data-driven Modelling and Digital Twins in Oncology: Implications in Experimental design and Clinical decision making
Cancer is a complex disease, with a variety of approaches available for its treatment, motivating a great unmet clinical need to enable more personalized therapy choices. The field of mathematical oncology approaches this question from multiple angles, including data-driven analysis of large-scale patient and experimental samples (e.g. imaging, or (multi-)omics characterization) and mechanistic descriptions (such as modelling of cancer evolution, therapy response, and progression) depending on the underlying data and specific task. As such, mathematical oncology is an interdisciplinary field wherein quantitative methods and tools are used to improve the understanding of cancer initiation, progression, and treatment. In the context of oncology applications, data-efficient algorithms, causal inference, and algorithm robustness as well as how to optimally harness the increasing amount of detailed patient-specific information are driving current research progress.
Active combinations of mechanistic and data-driven modelling are currently rare, likely due to a disconnect between the involved communities. This track aims to bring the mathematical modelling and data science communities together to develop enhanced methods of modelling and analysis centred around the principles of personalized oncology. In this context, we will prioritize implications in experimental designs, clinical decision support, and the generation of synthetic controls in the form of digital patient twins to explore alternative treatment protocols.
Submission format: this special session welcomes both full length papers (12 pages plus up to 2 pages of references) and abstracts (up to 3 pages including references).
Deadline: All deadlines, including submission deadline and review timeline are the same as the main conference. Please follow this link to see all the Important Dates.
If you have any questions regarding this Special Session, please contact the organiser.