大数据,大洞察:利用数据分析揭示心血管暴露体的复杂性。

Q2 Medicine
Methodist DeBakey cardiovascular journal Pub Date : 2024-11-05 eCollection Date: 2024-01-01 DOI:10.14797/mdcvj.1467
Ramzi Ibrahim, Hoang Nhat Pham, Khurram Nasir, Omar Hahad, Ashutosh Sabharwal, Sadeer Al-Kindi
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引用次数: 0

摘要

暴露体包括人一生中接触的各种环境,对心血管健康起着重要作用。暴露组中的社会、自然和人造成分之间的相互作用对心血管疾病的发病率和死亡率有重大影响。包括机器学习和地理空间分析在内的强大数据分析技术加深了我们对这些因素如何共同影响心血管疾病风险的理解。多组学平台与先进计算方法的整合提高了我们描述暴露组特征的能力,从而可采取有针对性的公共卫生干预措施和创新的降低风险策略,在全球范围内改善心血管健康状况。这些多组学平台整合了基因组学、表观基因组学、临床数据、社会因素、环境因素和可穿戴技术等因素,将更详细地描述与心血管健康有关的暴露组特征。在这篇综述中,我们旨在阐明暴露组的组成部分,并讨论有关它们与心血管健康关系的最新文献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big Data, Big Insights: Leveraging Data Analytics to Unravel Cardiovascular Exposome Complexities.

The exposome encompasses the full range of environmental exposures throughout a person's lifetime and plays an important role in cardiovascular health. Interactions with the social, natural, and built components of the exposome significantly impact cardiovascular disease prevalence and mortality. Robust data analytics, including machine learning and geospatial analysis, have advanced our understanding of how these factors converge to influence cardiovascular disease risk. The integration of multiomics platforms and advanced computational approaches enhances our ability to characterize the exposome, leading to targeted public health interventions and innovative risk reduction strategies aimed at improving cardiovascular health globally. These multiomics platforms that integrate factors such as genomics, epigenomics, clinical data, social factors, environmental factors, and wearable technology will characterize the exposome in greater detail concerning cardiovascular health. In this review, we aimed to elucidate the components of the exposome and discuss recent literature regarding their relationship to cardiovascular health.

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来源期刊
CiteScore
2.30
自引率
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发文量
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