The fifth RadExIORSBoost project training titled “Radiogenomics and basic principles of machine learning models in radiobiology” was successfully held from 18 to 20 May 2026 at the University of Leicester, United Kingdom. The training organized in a form of hybrid event gathered project team members from the Institute for Oncology and Radiology of Serbia (Dr. Ivana Matić, Dr. Nina Petrović, Dr. Marina Popović Krneta, and Dr. Branislava Gemović), Medical Faculty Mannheim, Heidelberg University (Prof. Dr. Marlon Veldwijk and Ahmad Šami), Institute of Oncology Ljubljana (Dr. Barbara Lisec) and host team from the University of Leicester led by Prof. Dr. Christopher Talbot (Prof. Dr. Christopher Talbot, Dr. Adam Webb, Dr. Tim Rattay, Dr. Bo Wang, and Prof. Dr. Huiyu Zhou).
The onsite and online training participants had the unique opportunity to acquire new state-of-the-art knowledge in machine learning-based modeling approaches in radiobiology, radiation oncology, and oncology through excellent lectures delivered by:
- Bo Wang on advanced statistical methods for longitudinal data;
- Dmitrii Lebedev on breast image analysis using AI;
- Tim Rattay on analysis of patient-reported outcomes- towards prediction modelling and intervention;
- Abeer Al-Janapy on machine learning approaches to predicting radiotherapy toxicity;
- Yang Hu on AI in computational pathology;
- Dr. Huiyu Zhou on AI methods for biomedical image processing;
- Genovefa Kefalidou on human computer interaction and evaluation;
- Vicki Emms on AI methods in PRE-ACT project;
- Adam Webb on machine learning and circadian rhythm effects;
- Dr. Christopher Talbot on applying agentic AI to clinical decision-making in the ABIGAIL4D project.
Team members also heard excellent presentations on biomarker development – from lab to clinic (Dr. Lynne Howells), a diagnostic ctDNA test for endometrial cancer (Dr. Esther Moss), the importance of liquid biopsies in cancer research (Dr. Becky Allsopp), and proteomics approaches (Prof. Dr. Don Jones). During the training, participants learned from the expert (Research and Enterprise Division from ULEIC) how to achieve impact in cancer research.
During the short-term training visit of the IORS team members from 18 May to 22 May 2026, the plans for the upcoming joint work on machine-learning prediction models were discussed with the UHEI and ULEIC team.
The RadExIORSBoost project team would like to thank Prof. Dr. Christopher Talbot and his team for excellent project training, knowledge transfer, expertise, and hospitality.
