




The next (and also the last) Consortium Meeting is starting!






The next (and also the last) Consortium Meeting is starting!

What is Capable Project?
The overall aim of CAPABLE is to combine the most advanced technologies for data and knowledge management with a sound socio-psychological approach in order to develop a coaching system for improving the quality of life of cancer home patients. The system aims at early detecting and managing cancer-related issues and at satisfying the needs of patients and their home caregivers.
CAPABLE project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 875052.

Latest News
Presentation at the AI in Healthcare Networking Event
CAPABLE project members participated in the “AI in Healthcare” networking event organized by the FAITH project on November 16, 2023 in Rome. Lucia Sacchi gave
7th Consortium Meeting in Madrid – Summary
The 7th Consortium Meeting is over ! Many thanks to Universidad Politecnica de Madrid (UPM) for organizing the event and showing us the beautiful city of
7th Consortium Meeting in Madrid
The next (and also the last) Consortium Meeting is starting! The 7th CM will be held in a hybrid mode in Madrid, Spain. Specifically, it
OVERALL GOAL

To develop a support system for improving the quality of life of cancer home patients by combining technologies for data and knowledge management with socio-psychological models and theories
MAIN OBJECTIVES
User Experience
- Identifying new patients’ and home caregivers’ needs
- Promoting patients’ engagement
- Improving patients’ compliance to treatment
- Facing patients’ emotional issues
- Supporting the use of computer-interpretable guidelines (CIGs) for healthcare professionals
- Improving clinical workflows
Technological
- Promoting data management through standard terminologies, data modeling, and FAIR principles
- Integrating (big) data coming from different sources
- Integrating data, knowledge and AI
- Using Health Technology Assessment as the basis for system development
Scientific
- Identifying gaps between clinical guidelines and patient needs
- Identifying new adverse effects
- Developing new models of disease course
- Managing Multimorbidity through CIG-based decision support
- Extending guideline formalization languages to include predictive models