HNN3.0

Project cooperationUpdated on 15 January 2026

Improving adherence to medical treatment through personalized messages

Professor at Crowdsourced Health lab at Bar Ilan University

Ramat Gan, Israel

About

We developed adaptive AI algorithms that learn to maximize adherence to medical treatment by matching the most effective messages to each individual.

Our work has been tested in clinical trials with diabetes patients, achieving up to 37% improvement in adherence to medication and a doubling of physical activity per week.

We are looking to scale up our efforts into additional populations and medical conditions.

Sample publications:

Topic

  • DESTINATION 1: HORIZON-HLTH-2026-01-STAYHLTH-02: Behavioural interventions as primary prevention for Non-Communicable Diseases (NCDs) among young people
  • DESTINATION 3: HORIZON-HLTH-2026-01-DISEASE-03: Advancing research on the prevention, diagnosis, and management of post-infection long-term conditions
  • DESTINATION 3: HORIZON-HLTH-2026-01-DISEASE-15: Scaling up innovation in cardiovascular health
  • DESTINATION 4: HORIZON-HLTH-2026-01-CARE-01: Public procurement of innovative solutions for improving citizens' access to healthcare through integrated or personalised approaches

Type

  • Partner seeks Consortium/Coordinator

Organisation

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