Exposomics and Cardiovascular Diseases: A Scoping Review of Machine Learning Approaches
Katerina D. Argyri,
Ioannis K. Gallos,
Angelos Amditis
et al.
Abstract:Cardiovascular disease has been established as the world’s number one killer, causing over 20 million deaths per year. This fact, along with the growing awareness of the impact of exposomic risk factors on cardiovascular diseases, has led the scientific community to leverage machine learning strategies as a complementary approach to traditional statistical epidemiological studies that are challenged by the highly heterogeneous and dynamic nature of exposomics data. The principal objective served by this work i… Show more
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