Summary
The main aim of FAITH is to apply the latest Artificial Intelligence (AI) and Big Data analytics techniques to better model and predict disease/treatment trajectories of cancer patients, with the goal of improving their quality of life and aftercare. To protect privacy of the individual, but still gain insights that are beneficial to the broader population, FAITH will be applying the concept of federated machine learning, which makes it possible to build machine learning systems without direct access to personal treatment data that will be used for training in machine learning. Devices private to the patient will run their own personalised AI models, via the project’s ‘AI Angel’ application, while a global AI model aggregates the individual model learnings (rather than the traditional approach of a central repository of holding all private patient data). FAITH’s ‘AI Angel’ will remotely analyse depression markers, predicting negative trends in their disease trajectory, giving their healthcare providers advanced warnings to allow for timely intervention. These markers are treated under several distinct categories: Activity, Outlook, Sleep, and Appetite, in accordance with the 3M strategy for population health: Monitor–Measure–Manage. Central to the vision of the FAITH project is to measure population health deeply, it is necessary to monitor individuals on a continuous basis to cast a wide enough net over a user’s health data. A key strength of FAITH is the involvement of eminent cancer hospitals and specialists in the consortium to provide relevant applicable cancer care related use cases that can effectively leverage a big data framework using computational intelligence approaches and methodologies that can be used for long term cancer care health risk and symptom minimisation for patients. FAITH has trial sites in Madrid, Waterford, and Lisbon, with real end users to assess and validate the adoption and usage of the FAITH technologies and platform.
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| Web resources: | https://cordis.europa.eu/project/id/875358 |
| Start date: | 01-01-2020 |
| End date: | 30-06-2024 |
| Total budget - Public funding: | 4 831 233,00 Euro - 4 831 233,00 Euro |
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Original description
The main aim of FAITH is to apply the latest Artificial Intelligence (AI) and Big Data analytics techniques to better model and predict disease/treatment trajectories of cancer patients, with the goal of improving their quality of life and aftercare. To protect privacy of the individual, but still gain insights that are beneficial to the broader population, FAITH will be applying the concept of federated machine learning, which makes it possible to build machine learning systems without direct access to personal treatment data that will be used for training in machine learning. Devices private to the patient will run their own personalised AI models, via the project’s ‘AI Angel’ application, while a global AI model aggregates the individual model learnings (rather than the traditional approach of a central repository of holding all private patient data). FAITH’s ‘AI Angel’ will remotely analyse depression markers, predicting negative trends in their disease trajectory, giving their healthcare providers advanced warnings to allow for timely intervention. These markers are treated under several distinct categories: Activity, Outlook, Sleep, and Appetite, in accordance with the 3M strategy for population health: Monitor–Measure–Manage. Central to the vision of the FAITH project is to measure population health deeply, it is necessary to monitor individuals on a continuous basis to cast a wide enough net over a user’s health data. A key strength of FAITH is the involvement of eminent cancer hospitals and specialists in the consortium to provide relevant applicable cancer care related use cases that can effectively leverage a big data framework using computational intelligence approaches and methodologies that can be used for long term cancer care health risk and symptom minimisation for patients. FAITH has trial sites in Madrid, Waterford, and Lisbon, with real end users to assess and validate the adoption and usage of the FAITH technologies and platform.Status
SIGNEDCall topic
SC1-DTH-01-2019Update Date
26-10-2022
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