The Future of Artificial Intelligence and Genetic Insights in Precision Cardiovascular Medicine: A Comprehensive Review

Abstract

Abstract A medical condition called cardiovascular disease (CVD) affects the heart or blood vessels, and about 40% of its causes can be attributed to genetic factors. The pathophysiology of CVD is still unknown despite numerous studies identifying important environmental and genetic factors. Genetic data research has significantly increased due to the application of genome-wide association studies. The utilization of artificial intelligence (AI) technology demonstrates clear advantages in managing intricate projects, outperforming traditional statistical methods in processing such data. The use of AI in the status of genetic research on CVD and medicine is briefly reviewed in the opening section of this article. Then, it gives a complete picture of how AI is used in genetic CVD research, including genetic data-driven diagnosis and prognosis, genetic variation analysis, gene expression profiles, gene interactions, and analysis of genes using knowledge bases. Even though much research has yielded significant findings, it is still early. The main disadvantages are database limitations, the underuse of AI in systematic biology analysis, and the lack of a theoretical framework for interpreting analysis results. The paper concludes with future directions and the significance of creating comprehensive, high-quality, large-sample-size data-sharing resources. Much research is going into how to use AI analysis techniques to help with development. Being creative with computers can help make new CVD intervention protocols and develop and test theoretical models.

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