1. Multiomics tools for improved atherosclerotic cardiovascular disease management.
- Author
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Sopic M, Vilne B, Gerdts E, Trindade F, Uchida S, Khatib S, Wettinger SB, Devaux Y, and Magni P
- Subjects
- Humans, Artificial Intelligence, Multiomics, Machine Learning, Cardiovascular Diseases diagnosis, Cardiovascular Diseases genetics, Cardiovascular Diseases therapy, Atherosclerosis diagnosis, Atherosclerosis genetics, Atherosclerosis therapy
- Abstract
Multiomics studies offer accurate preventive and therapeutic strategies for atherosclerotic cardiovascular disease (ASCVD) beyond traditional risk factors. By using artificial intelligence (AI) and machine learning (ML) approaches, it is possible to integrate multiple 'omics and clinical data sets into tools that can be utilized for the development of personalized diagnostic and therapeutic approaches. However, currently multiple challenges in data quality, integration, and privacy still need to be addressed. In this opinion, we emphasize that joined efforts, exemplified by the AtheroNET COST Action, have a pivotal role in overcoming the challenges to advance multiomics approaches in ASCVD research, with the aim to foster more precise and effective patient care., Competing Interests: Declaration of interests The authors declare no conflict of interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
- Published
- 2023
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