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KATY

Katy project
Full Title
Knowledge At the Tip of Your fingers: Clinical Knowledge for Humanity
Description

AI-empowered Personalized Medicine promises to find tailored, targeted, nearly “hand-made” cures for patients. Cancer treatment desperately needs boosters to find tailored, targeted cures for patients and Personalized Medicine can play a crucial role. Tailored targeted therapies in cancer treatment are already a reality but the current practice of targeted therapies in cancer treatment has been derived with traditional methods of data analysis. AI-empowered Personalized Medicine may help to bring targeted therapies to the next level. However, no matter how precise it is, no matter how many lives it can save in principle, and no matter if it can utilize the entire medical knowledge. If clinicians do not understand its suggestions and decisions, AI-empowered Personalized Medicine will not be a game-changer, clinicians will not use it to make everyday decisions and, thus, it is doomed to fail. Hence, the real challenge is building AI-empowered Personalized Medicine systems that can be accepted by clinicians and clinical researchers. In KATY, we grasp the above challenge and we propose an AI-empowered Personalized Medicine system that can bring medical “AI-empowered knowledge” to the tips of the fingers of clinicians and clinical researchers. The AI-empowered knowledge is a human interpretable knowledge that clinicians and clinical researchers can: understand, trust and effectively use in their everyday working routine. KATY is then an AI-empowered Personalized Medicine system built around two main components: A Distributed Knowledge Graph and A pool of eXplainable Artificial Intelligence predictors. As a stress test and due to the lack of personalized clinical responses, KATY will be experimented in a low prevalence and complex cancer: Clear cell renal cell carcinoma (ccRCC).

Funding Entity
EU H2020
Reference
Grant agreement ID: 101017453
Project Homepage
https://katy-project.eu/
Start Date
01/01/2021
End Date
31/12/2024
Coordinator
University of Rome Tor Vergata
Partners
LASIGE/FCiências.ID, CEA, Univ. Edinburgh, DS Tech, Uniw. Gdanski, Univ. St Andrews, Univ. Vienna, Eurecat, Eurice, OpenEvidence, Istituto. Nazionale dei Tumori, Lab4Life, Univ. Zaragoza, Personal Genomics, CHU Grenoble, Lunds Universitet, HPI, NKUA, NTUU KPI
Principal Investigator at LASIGE
Cátia Pesquita
Team at LASIGE
Status
Ongoing