Computational Models FOR patienT stratification in urologic cancers – Creating robust and trustworthy multimodal AI for health care

Aim

The COMFORT project (Computational Models FOR patienT stratification in urologic cancers – Creating robust and trustworthy multimodal AI for health care) aims to assist medical professionals in delivering improved care for people affected by prostate cancer or kidney cancer. The multidisciplinary research teams are developing a cutting-edge decision support system that uses artificial intelligence (AI) and data-driven insights.

The project strives to develop transparent and accurate computational models by integrating complex health data from multiple sources. These models will use advanced AI-powered risk stratification methods to help healthcare professionals select the right treatments, prevent disease progression, and improve the patient journey. Ultimately, the project will produce the first multi-national evaluation of AI models in a clinical setting and offer new insights to maximise the usefulness and acceptance of the technology.

Futher contact

For more information, see the COMFORT website or LinkedIn page.

Funding

This project is funded by the European Union.

People

Sarah de Boer

Sarah de Boer

PhD Candidate

Hartmut Häntze

Hartmut Häntze

PhD Candidate

Myrthe Buser

Myrthe Buser

Postdoctoral Researcher

Jen Dusseljee

Jen Dusseljee

Master Student

Alessa Hering

Alessa Hering

Assistant Professor

Publications

  • H. Häntze, L. Xu, F. Dorfner, L. Donle, D. Truhn, H. Aerts, M. Prokop, B. van Ginneken, A. Hering, L. Adams and K. Bressem, "MRSegmentator: Robust Multi-Modality Segmentation of 40 Classes in MRI and CT Sequences", arXiv:2405.06463, 2024.