Enhancing cardiovascular artificial intelligence (AI) research in the Netherlands: CVON-AI consortium

Area of Science:

• Cardiovascular Medicine
• Artificial Intelligence
• Machine Learning

Background:

• Machine learning (ML) offers advanced capabilities for analyzing complex, high-dimensional data, surpassing traditional statistical methods in classification and prediction.
• While AI and ML applications are rapidly advancing across various fields, their integration into cardiovascular medicine and research remains limited.
• The CVON-AI consortium aims to bridge this gap by fostering AI development and adoption in cardiovascular research.

Purpose of the Study:

• To establish the theoretical framework, objectives, and organizational structure of the novel CVON-AI consortium.
• To catalyze and facilitate the development and application of AI solutions within cardiovascular research initiatives.
• To enhance AI awareness and expertise within the cardiovascular research community.

Main Methods:

• Established the CVON-AI consortium, supported by the Netherlands Heart Foundation, to advance AI in cardiovascular research.
• Leveraged a cloud-based AI platform to complement existing data analysis approaches in cardiovascular research.
• Connected CVON-AI with previously established CVON consortia to promote collaboration and resource sharing.

Main Results:

• A pilot experiment utilizing the CVON-AI cloud platform with cardiac magnetic resonance imaging (cMRI) data demonstrated platform feasibility.
• AI-generated estimates of ventricular function showed excellent correlation with expert manual annotations.
• The developed AI solution was successfully integrated into a web application for broader accessibility.

Conclusions:

• CVON-AI is a newly formed consortium dedicated to facilitating AI implementation and raising awareness in Dutch cardiovascular research.
• The consortium will provide an accessible cloud-based platform for cardiovascular researchers.
• CVON-AI aims to showcase AI's clinical applicability, optimize analytical methods for ongoing research, and promote AI education and training.