Machine learning prediction and interpretability analysis of high-risk chest pain: a study from the MIMIC-IV database

Machine learning prediction and interpretability analysis of high-risk chest pain: a study from the MIMIC-IV database

BackgroundHigh-risk chest pain is a critical presentation in emergency departments, frequently indicative of life-threatening cardiopulmonary conditions. Rapid and accurate diagnosis is pivotal for improving patient survival rates.MethodsWe developed a machine learning prediction model using the MIM...

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Bibliographic Details
Main Authors: Hongyi Chen, Haiyang Song, Hongyu Huang, Xiaojun Fang, Huang Chen, Qingqing Yang, Junyu Zhang, Wenjun Ding, Zheng Gong, Jun Ke
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Physiology
Subjects:
bayesian optimization
model interpretability
high-risk chest pain prediction
MIMIC-IV
machine learning (ML)
Online Access:https://www.frontiersin.org/articles/10.3389/fphys.2025.1594277/full
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https://www.frontiersin.org/articles/10.3389/fphys.2025.1594277/full

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