Enhancing cardiovascular artificial intelligence (AI) research in the Netherlands: CVON-AI consortium.
Artificial intelligence
CVON-AI consortium
Cardiovascular disease
Machine learning
Journal
Netherlands heart journal : monthly journal of the Netherlands Society of Cardiology and the Netherlands Heart Foundation
ISSN: 1568-5888
Titre abrégé: Neth Heart J
Pays: Netherlands
ID NLM: 101095458
Informations de publication
Date de publication:
Sep 2019
Sep 2019
Historique:
pubmed:
22
5
2019
medline:
22
5
2019
entrez:
22
5
2019
Statut:
ppublish
Résumé
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. To lay out the theoretical framework, purpose, and structure of a novel AI consortium. 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. 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. 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.
Sections du résumé
BACKGROUND
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
OBJECTIVE
To lay out the theoretical framework, purpose, and structure of a novel AI consortium.
METHODS
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
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
CONCLUSIONS
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.
Identifiants
pubmed: 31111459
doi: 10.1007/s12471-019-1281-y
pii: 10.1007/s12471-019-1281-y
pmc: PMC6712143
doi:
Types de publication
Journal Article
Langues
eng
Pagination
414-425Subventions
Organisme : Hartstichting
ID : 2018B017
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