Published October 18, 2022 | Version v1
Conference paper Open

iHELP: Personalised Health Monitoring and Decision Support Based on Artificial Intelligence and Holistic Health Records

  • 1. University of Piraeus
  • 2. Innovation Sprint
  • 3. Universidad Politécnica de Madrid
  • 4. Fondazione Policlinico Universitario Agostino Gemelli IRCCS
  • 5. Hospital de Dénia-MarinaSalud
  • 6. Athens Technology Centre
  • 7. KODAR Systems
  • 8. Medical University Plovdiv
  • 9. LeanXcale
  • 10. University of Manchester
  • 11. Taipei Medical University
  • 12. Engineering Ingegneria Informatica SpA
  • 13. Siemens SRL
  • 14. Karolinska Institutet
  • 15. Information Catalyst for Enterprise

Description

Scientific and clinical research have advanced the ability of healthcare professionals to more precisely define diseases and classify patients into different groups based on their likelihood of responding to a given treatment, and on their future risks. However, a significant gap remains between the delivery of stratified healthcare and personalization. The latter implies solutions that seek to treat each citizen as a truly unique individual, as opposed to a member of a group with whom they share common risks or health-related characteristics. Personalisation also implies an approach that takes into account personal characteristics and conditions of individuals. This paper investigates how these desirable attributes can be developed and introduces a holistic environment, the iHELP, that incorporates big data management and Artificial Intelligence (AI) approaches to enable the realization of data-driven pathways where awareness, care and decision support is provided based on person-centric early risk prediction, prevention and intervention measures.

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Additional details

Funding

European Commission
iHELP – Personalised Health Monitoring and Decision Support Based on Artificial Intelligence and Holistic Health Records 101017441