Skip to main content
Go to the home page of the European Commission (opens in new window)
English English
CORDIS - EU research results
CORDIS

AI supported picture analysis in large bowel camera capsule endoscopy

Project description

AI algorithms to advance novel low-invasive endoscopy procedures

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.

Objective

"Millions of Europeans undergo optical colonoscopy (OC) every year as a part of diagnostic procedures for bowel issues such as possible bowel cancer. For citizens and patients OC is associated with discomfort, possible complications and sick-days from work, which affects the acceptability to undergo the procedure. OC also constitutes a heavy burden on European hospital capacities.
Colon capsule endoscopy (CCE) is a technology that has the potential to replace a substantial proportion of OCs. Studies have shown that CCE is preferred by patients over OC, has a lower complication rate and can be performed out of hospital, in the home of the patient. Thus, CCE holds great potential for both patients and hospitals.
However, the current diagnostic process of CCE includes a time-consuming manual reading of the images captured by the capsule (the so-called ""camera pill"") done by trained medical staff, which is both expensive and prone to human error. For CCE to be a viable alternative to OC in clinical practice, these challenges need to be addressed.
Therefore, the goal of the AICE project is to develop and validate a set of artificial intelligence algorithms that can assist in the reading of the CCE images to ensure both high quality diagnostics and save crucial clinical resources.
The AICE project aims to create a complete and validated AI-assisted pathway that improves CCE diagnostics making the technology clinically viable for the good of patients, health care systems and society.

A number of the partners in AICE have been collaborating for a number of years and have completed development of several AI algorithms (AIA) for CCE diagnostics that are now in need of external clinical validation. More algorithms will be completed and prepared for validation within the first 2 years of the AICE project.

The AICE concept will focus on:

1) completing development of the remaining AIAs,
2) external validation of all of the AICE AIAs,
3) creating a clinical support system for data handling, storage and transmission,
4) developing a diagnostic pathway that considers quality, efficiency, patient preferences, ethics and economy
5) promotes the integration of AICE solutions into clinical practice via implementation guidelines and upscaling adjustments.

To achieve these goals, AICE will use an unprecedented large and diverse collection of existing patient data from nation-wide clinical studies, and will include extensive initiatives in the fields of ethics, communication and patient engagement. To ensure the right competences are present, AICE brings together clinical researchers, epidemiologists, data scientists, digital health experts, health economists, ethics researchers, SMEs, communication experts and experts in regulatory affairs."

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been validated by the project's team.

Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-RIA - HORIZON Research and Innovation Actions

See all projects funded under this funding scheme

Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-HLTH-2021-DISEASE-04

See all projects funded under this call

Coordinator

REGION SYDDANMARK
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 771 148,75
Address
DAMHAVEN 12
7100 Vejle
Denmark

See on map

Region
Danmark Syddanmark Sydjylland
Activity type
Public bodies (excluding Research Organisations and Secondary or Higher Education Establishments)
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 771 151,25

Participants (8)

Partners (4)

My booklet 0 0