FAITH aims to provide an Artificial Intelligence application that remotely identifies depression markers, using Federated Learning, in people that have undergone cancer treatment to better model and predict disease/treatment trajectories. 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. 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. FAITH has trial sites in Madrid, Waterford, and Lisbon, with real end users involved in assessing and validating the AI application to ensure its usefulness.

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Other resources: https://cordis.europa.eu/project/id/875358