COMputational Models FOR patienTstratification in urologic cancers – Creating robust and trustworthy multimodal AI for health care (COMFORT)
In Europe, more than two million men are living with prostate cancer (PCa), and about 80,000 die from it each year. To date, there are no accurate, robust, transparent and ready-to-use multimodal AI tools for PCa and KC and no standard-of-care options for non-invasive individual patient stratification according to prognosis and therapy response at the time of initial diagnosis. Current standard diagnostic procedures for PCa have led to overdiagnosis and overtreatment, while at the same time resulting in under- or missed diagnosis. For low-grade PCa, e.g., aggressive therapy can result in long-term side effects, such as sexual dysfunction or incontinence.
COMFORT sets out to develop and prospectively validate data-driven decision support tools based on cutting edge AI models, to improve detection, diagnosis and prognosis of patients with PCa and KC.
Partners:
- Charité Berlin - Department of Radiology and Comprehensive Cancer Center, Berlin, DE
- University of Naples "Federico II" - Department of Radiology, IT
- Technical University Munich - Department of Radiology and Institute for Artificial Intelligence in Healthcare and Medicine, DE
- General University Hospital of Patras - Department of Urology, GR
- School of Medicine of the Aristotle University of Thessaloniki (A.U.Th) - 1st Department of Urology, Laboratory of Medical Physics and Digital Innovation, GR
- Servicio Madrileno de Salud, ES
- Hospital 12 de Octubre, Departament of Medical Oncology, ES
- Berlin University of Applied Sciences and Technology (BHT) - Data Science +X Research Center, DE
- Radboud University Medical Center Nijmegen (Radboudumc), NL
- Quantib B.V., NL
- Phönix PACS GmbH - PACS provider, DE
- European Research and Project Office GmbH, DE
- Umeå University - Responsible Artificial Intelligence, SE
- European Cancer Patient Coalition, BE
- MeVis Medical Solutions AG, DE
Funded by:
EU-HORIZON-HLTH-2020
Project duration:
2023-2027