Scholarlink

<p>Cardiovascular risk stratification is crucial, as it is a key predictor of morbidity and mortality. The development of multiparametric scores for coronary risk stratification, integrated with artificial intelligence (AI), is important because it facilitates assessment in clinical practice. Therefore, prognostic coronary risk scores that incorporate multiple clinical variables and cardiac imaging data are necessary and deserve greater attention, as they provide a more comprehensive and accurate evaluation of individual patient risk across various clinical scenarios. Additionally, they support clinicians in making better-informed decisions based on a comprehensive assessment. Importantly, the widespread clinical use of multiparametric risk scores should be enabled by implementing standardized computer interfaces that can exchange the relevant imaging and clinical data needed to calculate these scores. The ongoing AI revolution, which increasingly relies on digital demographic, clinical, and imaging data, is rapidly making the availability of such data a reality.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

The importance of developing multiparametric prognostic scores to stratify coronary risk by means of artificial intelligence

  • 期刊论文

  • 发表日期：

    2025年8月29日

查看全文
  • Guillermo Romero-Farina,
  • Santiago Aguadé-Bruix,
  • C. David Cooke,
  • Ernest V. Garcia

摘要

Cardiovascular risk stratification is crucial, as it is a key predictor of morbidity and mortality. The development of multiparametric scores for coronary risk stratification, integrated with artificial intelligence (AI), is important because it facilitates assessment in clinical practice. Therefore, prognostic coronary risk scores that incorporate multiple clinical variables and cardiac imaging data are necessary and deserve greater attention, as they provide a more comprehensive and accurate evaluation of individual patient risk across various clinical scenarios. Additionally, they support clinicians in making better-informed decisions based on a comprehensive assessment. Importantly, the widespread clinical use of multiparametric risk scores should be enabled by implementing standardized computer interfaces that can exchange the relevant imaging and clinical data needed to calculate these scores. The ongoing AI revolution, which increasingly relies on digital demographic, clinical, and imaging data, is rapidly making the availability of such data a reality.