Project description
Cancer prevention: the role of artificial intelligence
Colonoscopy constitutes the conventional approach for detecting and removing precancerous polyps. Although artificial intelligence (AI) is considered to assist the detection of malignant cells, there is no direct evidence of its impact on colorectal cancer prevention. The key objective of the EU-funded ACCEPT project is to establish the research infrastructure which enables direct comparison between standard colonoscopy and AI-assisted colonoscopy. Researchers will utilise real-world data as well as follow-up information from the national colorectal cancer screening programmes in Europe. Results will provide reliable evidence on the role of AI in cancer prevention and help disseminate this technology across Europe and the rest of the world.
Objective
Removal precancerous polyps (so-called adenomas) during colonoscopy reduces colorectal cancer incidence and mortality. We have recently developed artificial intelligence (AI) systems which optimise colonoscopy quality by aiming at increasing the detection of adenomas. However, it is unknown if this benefit of AI translates into improved cancer prevention.
To establish the role of AI in colorectal cancer prevention, we here propose a three-step research portfolio targeting individuals in the national colorectal cancer screening programmes in Norway and Poland. 1) A 1-year observational study to clarify the superiority of AI in adenoma detection in the average-risk population. 2) A cost-effectiveness analysis for cancer prevention, using real-world data obtained from the part 1 study. 3) Establishment of an infrastructure for long-term (10 years) follow-up of 40,000 individuals to quantify the effect of AI on colorectal cancer incidence.
We use propensity score matching to balance the background characteristics of the two comparing arms; AI-assisted colonoscopy and standard colonoscopy. Participants are followed through national cancer registries for ten years after cancer screening.
Our project is the first of its kind and made possible by the unique collaboration of world-class environments in clinical epidemiology and medical device assessment with world-leading AI developers. The project will enable evidence-based implementation of AI technologies into nationwide cancer screening programmes in Europe and the world.
The project’s achievement will be maximised through detailed plans for training, monitoring, management, exploitation, dissemination, and communication. While adding essential competence to the host institution, this project will increase the applicant’s skill, especially in epidemiologic aspects, helping him obtain an independent academic position in translational research of AI for medicine.
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.
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.
- natural sciences computer and information sciences artificial intelligence
- social sciences sociology demography mortality
- medical and health sciences health sciences public health epidemiology
- medical and health sciences clinical medicine oncology colorectal cancer
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
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.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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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.
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.
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.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2020
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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.
0313 Oslo
Norway
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.