Publication
FEDWELL: Life-Long Federated User and Mental Modeling for Health and Well-being
Sabine Janzen; Prajvi Saxena; Cicy Agnes; Muhammad Ebad Ullah Khan; Amr Gomaa; Michael Feld; André Zenner; Pascal Lessel; Julian Wolter; Florian Daiber; Rafael Math; Niko Kleer; Tim Schwartz; Antonio Krüger; Wolfgang Maaß
In: RPEatCAiSE25: Research Projects Exhibition at the International Conference on Advanced Information Systems Engineering, June 16-20, 2025, Vienna, Austria. International Conference on Advanced Information Systems Engineering (CAiSE-2025), 6/2025.
Abstract
Adaptive and personalized AI systems in healthcare rely on user-specific and contextual information to provide
support. However, incomplete, unreliable, and outdated data prevents both patients experiencing illness, pain, or
cognitive impairment, as well as therapists, in making proper and informed decisions. Patients specifically may
not have the knowledge to comprehend complex medical information, or effectively communicate symptoms. AI-
driven mental models and user models can bridge these cognitive gaps, ensuring personalized and effective patient
care. The FedWell research project (09/2023–08/2026), funded by the Federal Ministry of Education and Research
(BMBF), explores the integration of artificial mental models (AMMs) and user models from various sources
into adaptive AI systems to assist patients in decision-making. The project focuses on two key applications:
rehabilitation support after knee/hip surgery and treatment decision assistance for patients with cognitive
impairments (e.g., multiple sclerosis, dementia). FedWell employs a combination of structured surveys, contextual
data collection, and AI techniques to model patient behavior, attitudes, and intentions. A decision support system
MENTALYTICS is developed from fine-tuned large language models (LLaMA-2, LLaMA-3, Mistral, Phi-3), that
employs AMMs. By the end of the project, FedWell aims to deliver robust AMMs capable of representing patient
beliefs and decision-making processes, ultimately guiding them toward treatment options that best fit their
individual needs.