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Updated: Jun 11, 2025

A Data-Driven Approach to Quantifying Immune States in Sepsis
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A Data-Driven Approach to Quantifying Immune States in Sepsis

Published on: February 7, 2025

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开发和验证毒症风险指数,支持早期识别ICU获得的毒症:一项观察性研究

Scott M Pappada1, Mohammad Hamza Owais2, John J Feeney3

  • 1Department of Anesthesiology, The University of Toledo College of Medicine and Life Sciences, Toledo, OH 43614, USA; Department of Bioengineering, The University of Toledo, Toledo, OH 43606, USA; Department of Electrical Engineering and Computer Science, The University of Toledo, Toledo, OH 43606, USA.

Anaesthesia, critical care & pain medicine
|October 4, 2024
PubMed
概括

一个新的败血症风险指数 (SRI) 使用机器学习来帮助医疗保健提供者早期检测败血症和败血症休克. 这种0-100标志物有助于及时诊断和干预这种危及生命的疾病.

关键词:
人工智能的人工智能是人工智能.临床决策支持 临床决策支持机器学习是机器学习.预测性诊断是一种预测性诊断.败血症 这是一种败血症.败血症的冲击是一个令人震惊的现象.

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