Building TrustworthyDigital Twins for Patient-Centred Medicine
About us
The diagnosis and monitoring of patients rely on a wide range of heterogeneous data sources: medical imaging, laboratory results, information on health risk factors, and clinical reports derived from consultations with patients. Bringing together these diverse types of information and drawing meaningful conclusions from them is a highly time-consuming task, often reducing the time physicians can spend in direct contact with their patients. In addition, the fragmentation of health data can also lead to delays in follow-up examinations and interventions, which may significantly worsen outcomes for patients at risk.
TWIN-X aims to address these challenges through the use of artificial intelligence. The project pursues the vision of developing a trustworthy and explainable AI model that unlocks new opportunities for personalised medicine and research in Europe. By integrating diverse health data into a comprehensive digital twin, TWIN-X seeks to support clinicians in making more informed decisions in the treatment of cardiovascular and oncological diseases.
01/06/2026
Start date
48 months
of duration
15 MIL €
Budget
19 Partners
From 13 countries
Digital Twins in Medicine
Digital twins are emerging as a powerful new approach in healthcare. By combining data from medical imaging, laboratory tests, patient records, and other sources, AI can create virtual representations of individual patients and simulate how diseases may develop or respond to treatment. This enables more accurate diagnoses, more personalised treatment decisions, and a deeper understanding of complex conditions such as cancer and cardiovascular disease.
