Multiomics tools for improved atherosclerotic cardiovascular disease management

on behalf of EU-AtheroNET COST Action CA21153

Research output: Contribution to journalReview articlepeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)983-995
Number of pages13
JournalTrends in Molecular Medicine
Volume29
Issue number12
Early online date6 Oct 2023
DOIs
Publication statusPublished - Dec 2023

Keywords

  • artificial intelligence
  • atherosclerotic cardiovascular disease
  • data integration
  • machine learning
  • multiomics

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