Benjamins, JW;
van Leeuwen, K;
Hofstra, L;
Rienstra, M;
Appelman, Y;
Nijhof, W;
Verlaat, B;
... van der Harst, P; + view all
(2019)
Enhancing cardiovascular artificial intelligence (AI) research in the Netherlands: CVON-AI consortium.
Netherlands Heart Journal
, 27
(9)
pp. 414-425.
10.1007/s12471-019-1281-y.
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Abstract
Background Machine learning (ML) allows the exploration and progressive improvement of very complex high-dimensional data patterns that can be utilised to optimise specific classification and prediction tasks, outperforming traditional statistical approaches. An enormous acceleration of ready-to-use tools and artificial intelligence (AI) applications, shaped by the emergence, refinement, and application of powerful ML algorithms in several areas of knowledge, is ongoing. Although such progress has begun to permeate the medical sciences and clinical medicine, implementation in cardiovascular medicine and research is still in its infancy. Objectives To lay out the theoretical framework, purpose, and structure of a novel AI consortium. Methods We have established a new Dutch research consortium, the CVON-AI, supported by the Netherlands Heart Foundation, to catalyse and facilitate the development and utilisation of AI solutions for existing and emerging cardiovascular research initiatives and to raise AI awareness in the cardiovascular research community. CVON-AI will connect to previously established CVON consortia and apply a cloud-based AI platform to supplement their planned traditional data-analysis approach. Results A pilot experiment on the CVON-AI cloud was conducted using cardiac magnetic resonance data. It demonstrated the feasibility of the platform and documented excellent correlation between AI-generated ventricular function estimates as compared to expert manual annotations. The resulting AI solution was then integrated in a web application. Conclusion CVON-AI is a new consortium meant to facilitate the implementation and raise awareness of AI in cardiovascular research in the Netherlands. CVON-AI will create an accessible cloud-based platform for cardiovascular researchers, demonstrate the clinical applicability of AI, optimise the analytical methodology of other ongoing CVON consortia, and promote AI awareness through education and training.
| Type: | Article |
|---|---|
| Title: | Enhancing cardiovascular artificial intelligence (AI) research in the Netherlands: CVON-AI consortium |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s12471-019-1281-y |
| Publisher version: | https://doi.org/10.1007/s12471-019-1281-y |
| Language: | English |
| Additional information: | This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
| Keywords: | Machine learning, Artificial intelligence, Cardiovascular disease, CVON-AI consortium |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10081739 |
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