KATY | Knowledge At the Tip of Your fingers: Clinical Knowledge for Humanity

Summary
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 a 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).
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101017453
Start date: 01-01-2021
End date: 31-12-2024
Total budget - Public funding: 8 479 900,00 Euro - 8 479 900,00 Euro
Cordis data

Original 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 a 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).

Status

SIGNED

Call topic

DT-TDS-04-2020

Update Date

26-10-2022
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Horizon 2020
H2020-EU.3. SOCIETAL CHALLENGES
H2020-EU.3.1. SOCIETAL CHALLENGES - Health, demographic change and well-being
H2020-EU.3.1.0. Cross-cutting call topics
H2020-SC1-FA-DTS-2020-1
DT-TDS-04-2020 AI for Genomics and Personalised Medicine