A primer in artificial intelligence in cardiovascular medicine

Driven by recent developments in computational power, algorithms and web-based storage resources, machine learning (ML)-based artificial intelligence (AI) has quickly gained ground as the solution for many technological and societal challenges. AI education has become very popular and is oversubscri...

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Bibliographic Details
Published in:Netherlands heart journal 2019-09, Vol.27 (9), p.392-402
Main Authors: Benjamins, J. W., Hendriks, T., Knuuti, J., Juarez-Orozco, L. E., van der Harst, P.
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Cardiology
Classification
Datasets
Decision trees
Deep learning
Electrocardiography
Expected utility
Machine learning
Medical Education
Medicine
Medicine & Public Health
Neural networks
Review
Review Article
Support vector machines
Variables
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Summary:Driven by recent developments in computational power, algorithms and web-based storage resources, machine learning (ML)-based artificial intelligence (AI) has quickly gained ground as the solution for many technological and societal challenges. AI education has become very popular and is oversubscribed at Dutch universities. Major investments were made in 2018 to develop and build the first AI-driven hospitals to improve patient care and reduce healthcare costs. AI has the potential to greatly enhance traditional statistical analyses in many domains and has been demonstrated to allow the discovery of ‘hidden’ information in highly complex datasets. As such, AI can also be of significant value in the diagnosis and treatment of cardiovascular disease, and the first applications of AI in the cardiovascular field are promising. However, many professionals in the cardiovascular field involved in patient care, education or science are unaware of the basics behind AI and the existing and expected applications in their field. In this review, we aim to introduce the broad cardiovascular community to the basics of modern ML-based AI and explain several of the commonly used algorithms. We also summarise their initial and future applications relevant to the cardiovascular field.
ISSN:1568-5888
1876-6250
DOI:10.1007/s12471-019-1286-6