AI supported picture analysis in large bowel camera capsule endoscopy

  • Torres, Ferran (Principal Investigator)
  • Carot Sans, Gerard (Collaborator)
  • Valero Bover, Damià (Collaborator)
  • Piera Jiménez, Jordi (Investigator)
  • Pontes Garcia, Caridad (Investigator)
  • González Amezcua, Aitor (Investigator)

Project Details

Description

Colon capsule endoscopy (CCE) is a new technology with the potential to replace most of the current optical colonoscopy procedures, which are associated with discomfort and complications. The CCE has a lower complication rate and does not require a hospital setting but includes a time-consuming manual reading and is prone to human error. The EU-funded AICE project aims to create an AI-supported pathway for CCE diagnostics, making it clinically viable. The AICE will use a diverse collection of existing patient data to complete and validate the AI algorithms for CCE diagnostics, create a clinical support system for data handling, storage and transmission and promote the integration of the AICE solution into clinical practice.
AcronymAICE
StatusActive
Effective start/end date1/09/2231/08/26

Collaborative partners

  • Universitat Autònoma de Barcelona (UAB)
  • Region of Southern Denmark (Coordinator) (lead)
  • University of Southern Denmark (Syddansk Universiteit) (Project partner)
  • Sundhed.dk (SDK) (Project partner)
  • Stratos AI (Stra) (Project partner)
  • Lund University (Project partner)
  • National and Kapodistrian University of Athens (NKUA) (Project partner)
  • University of Tromsoe (Project partner)
  • Umeå University (Project partner)
  • Catalan Health Service (CatSalut) (Project partner)

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

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