AI for Health Imaging
Call text (as on F&T portal)
View on F&T portalArtificial Intelligence (AI) offers substantial opportunities for healthcare, supporting better diagnosis, treatment, prevention and personalised care. Analysis of health images is one of the most promising fields for applying AI in healthcare, contributing to better prediction, diagnosis and treatment of diseases. In order to develop and test reliable AI applications in the field, access to large-volume of high- quality data is needed.
Scope
This action should contribute to testing and developing AI tools and analytics focused on the prevention, prediction and treatment of the most common forms of cancer while providing solutions to securely share health images across Europe.
Proposals should set up and contribute to populate a large interoperable repository of health images, enabling the development, testing and validation of AI–based health imaging solutions to improve diagnosis, disease prediction and follow-up of the most common forms of cancer[1].
The repository should include high quality, interoperable, anonymised or pseudo-anonymised data sets of annotated cases, based on data donorship, and should comply with relevant ethics, security requirements and data protection legislation. Gender aspects should be considered appropriately. It should ensure data quality and interoperability based on common standards and open Application Programming Interfaces (APIs).
Proposers should specify measures for validating AI-based solutions for health images, such as the effectiveness of clinical decision making. There should be rigorous, peer-reviewed scientific evidence establishing their safety, validity, reproducibility, usability, reliability and usefulness for better health outcomes. It is critical to show how AI-based solutions will deal with and inform about possible failures, inaccuracies and errors. Adequate performance metrics, monitoring and evaluation criteria and procedures should be put in place. The reasoning behind AI-based conclusions and recommendations should be explained so that users can understand their situation and be able to consent or challenge any proposed course of action.
The consortium should build on relevant national and EU activities and bring together: 1) expertise to set up the infrastructure, ensuring the appropriate sharing of data quality and interoperability, 2) AI developers/expertise to experiment its content while ensuring compliance with relevant legislations
The Commission considers that proposals requesting from the EUR 8 -10 million would allow this specific challenge to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts.
Expected Impact:The proposal should provide appropriate indicators to measure its progress and specific impact in the following areas:
- Contributing towards the creation of a EU-wide repository of health images dedicated to the most common forms of cancer, enabling experimentation of AI-based solutions to improve diagnosis, treatment and follow-up and contribute to a more precise and personalised management of cancer.
- Contributing to developing technical, organisational and ethical standards for AI for health imaging
- Promoting access to anonymised health image data sets to be made more openly reusable across the EU for training AI applications.
- Increasing trust in AI solutions among users (healthcare professionals and patients), investors and stakeholders at industry and academia.
Open ScienceOpen InnovationGender
[1]As reported by the World Health Organisation, see for example https://www.who.int/news-room/fact-sheets/detail/cancer
News flashes
An overview of the evaluation results (called 'Call results') of topic DT-TDS-04-2020 is now available under section Topic conditions and documents
NB: The evaluation form for topic DT-TDS-04-2020 (RIA) has been adapted from the standard format to a specific format in order to reflect the specific criteria scoring as set up in the Work Programme.
Please note that the submission deadline for this topic has been extended from 22 April to 18 June 2020. This extension is a response to the COVID-19 crisis that has severely affected many potential applicants of this topic, to allow more time for proposal preparation. Depending on how the COVID-19 situation evolves, a further extension to the June deadline may be considered and would be communicated in due time.
An overview of the evaluation results (called 'Call results') of topic DT-TDS-05-2020 is now available under section Topic conditions and documents -
34 proposals have been submitted in response to this call with deadline 13th of November 2019.The number of submissions per topic are:
Topic Action N° proposals
DT-TDS-05-2020 RIA 34
Topic code Topic short name Overall threshold applied SU-TDS-02-2018 Toolkit for assessing and reducing cyber risks in hospitals and care centres to protect privacy/data/infrastructures 10 SU-TDS-03-2018 Raising awareness and developing training schemes on cybersecurity in hospitals 10
The results of the evaluation are as follows: SU-TDS-02-2018Number of proposals submitted (including proposals transferred from or to other calls): 42Number of inadmissible proposals: 1Number of ineligible proposals: 0Number of above-threshold proposals: 25Total budget requested for above-threshold proposals: 112,361,970.25€SU-TDS-03-2018Number of proposals submitted (including proposals transferred from or to other calls): 5Number of inadmissible proposals: 0Number of ineligible proposals: 0Number of above-threshold proposals: 3Total budget requested for above-threshold proposals: 2,996,512.5€Total call budget requested for above-threshold proposals: 115,358,482.75€We recently informed the applicants about the evaluation results for their proposals.Research Enquiry Service
Due to some technical problems encountered with the submission proposals, the deadline of this call has been extended to Wednesday 25th of April @ 17:00hrsCEST.
We bring to your attention the following notice regarding page limits applicable to proposals.
Applicants are allowed to remove the page break in the cover page of the template for the technical annex,i.e. the proposal text can start on the cover page.
Opening date: 2019-07-09 (7 years ago)
Closing date: 2019-11-13 (6 years ago)
Procedure: single-stage
Budget: 35,000,000
Expected grants: not specified
This call topic has been appended 15 times by the EC with news.
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2020-10-16
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2020-05-25
nb: the evaluation form for topic dt-tds... -
2020-04-08
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2020-04-02
an overview of the evaluation results (c... -
2020-03-26
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2019-11-26
34 proposals have been submitted in resp... -
2019-11-19
the submission session is now available... -
2019-07-09
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2018-08-10
published: 27.10.2017deadline: 25.04.201... -
2018-07-26
the submission session is now available... -
2018-05-16
a total of 42riaand 5csa proposals were... -
2018-04-24
due to some technical problems encounter... -
2018-04-24
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2018-03-01
we bring to your attention the following... -
2017-11-07
the submission session is now available...
H2020-SC1-FA-DTS-2018-2020
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Timeline
Call published · 30 Sep 2024 (2 years ago)
All expected milestones for this call have passed.
Work programme published
27 Aug 2017 · est.
Call opens
09 Jul 2019
Call closes
13 Nov 2019
Outcome expected
13 Apr 2020 · est.
Grant agreement signed
13 Jul 2020 · est.
Call published
30 Sep 2024
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Work programme published Estimated
27 Aug 2017 · 9 years ago
Topics are listed in the Work Programme before the call opens. Spotting this early gives you a head start on partner search and proposal planning.
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Call opens
09 Jul 2019 · 7 years ago
Submissions can be made from this date.
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Call closes
13 Nov 2019 · 6 years ago
Deadline to submit a proposal.
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Outcome expected Estimated
13 Apr 2020 · 6 years ago
The maximum time to inform applicants of the evaluation outcome is five months after the call closes.
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Grant agreement signed Estimated
13 Jul 2020 · 6 years ago
The maximum time to sign the grant agreement is three months after applicants are informed of the outcome.
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Call published
30 Sep 2024 · 2 years ago
This topic was first published in TopicTree.
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