Improving the diagnosis of myocardial infarction with machine learning

被引：4

作者：

Doudesis, Dimitrios ^{[1
]}

Mills, Nicholas L. ^{[1
]}

机构：

[1] Univ Edinburgh, Edinburgh, Scotland

来源：

NATURE MEDICINE | 2023年 / 29卷 / 05期

关键词：

D O I：

10.1038/s41591-023-02331-6

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

Machine learning models that integrate cardiac troponin concentrations and clinical features to compute the probability of myocardial infarction outperform current care pathways that use fixed troponin thresholds or risk scores. Adoption of these models could reduce inequalities, prevent unnecessary admissions, and accelerate the diagnosis and treatment of patients with myocardial infarction.

引用

页码：1070 / 1071

页数：2

共 5 条

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