Artificial intelligence–based predictive models in vascular diseases

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Fabien Lareyre , Arindam Chaudhuri , Christian-Alexander Behrendt , Alexandre Pouhin , Martin Teraa , Jonathan R. Boyle , Riikka Tulamo , Juliette Raffort
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引用次数: 0

Abstract

Cardiovascular disease represents a source of major health problems worldwide, and although medical and technical advances have been achieved, they are still associated with high morbidity and mortality rates. Personalized medicine would benefit from novel tools to better predict individual prognosis and outcomes after intervention. Artificial intelligence (AI) has brought new insights to cardiovascular medicine, especially with the use of machine learning techniques that allow the identification of hidden patterns and complex associations in health data without any a priori assumptions. This review provides an overview on the use of artificial intelligence–based prediction models in vascular diseases, specifically focusing on aortic aneurysm, lower extremity arterial disease, and carotid stenosis. Potential benefits include the development of precision medicine in patients with vascular diseases. In addition, the main challenges that remain to be overcome to integrate artificial intelligence–based predictive models in clinical practice are discussed.

基于人工智能的血管疾病预测模型
心血管疾病是全世界主要健康问题的一个根源,尽管在医学和技术方面取得了进步,但它们仍然与高发病率和死亡率有关。个性化医疗将受益于新的工具,以更好地预测个体预后和干预后的结果。人工智能(AI)为心血管医学带来了新的见解,特别是机器学习技术的使用,可以在没有任何先验假设的情况下识别健康数据中的隐藏模式和复杂关联。本文综述了基于人工智能的预测模型在血管疾病中的应用,特别是在主动脉瘤、下肢动脉疾病和颈动脉狭窄方面。潜在的好处包括发展血管疾病患者的精准医学。此外,还讨论了在临床实践中整合基于人工智能的预测模型需要克服的主要挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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