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Updated: Jul 1, 2025

A Data-Driven Approach to Quantifying Immune States in Sepsis
07:42

A Data-Driven Approach to Quantifying Immune States in Sepsis

Published on: February 7, 2025

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在第一波COVID-19患者开发的无监督集群模型在第二/第三波危急病患者中的适用性

Alejandro Rodríguez1, Josep Gómez2, Álvaro Franquet2

  • 1Critical Care Department - Hospital Universitari de Tarragona Joan XXIII, Tarragona, Spain; Universidad Rovira & Virgili/Institut d'Investigació Sanitaria Pere Virigili/CIBERES, Tarragona, Spain.

Medicina intensiva
|March 10, 2024
PubMed
概括

针对COVID-19患者表型的机器学习模型需要在不同的流行浪潮中进行验证. 在大流行早期开发的无监督集群模型在后来的波浪中表现不佳,需要新的波浪特定模型.

关键词:
自动学习是一种自动学习.风险因素 风险因素现象类型 现象类型严重感染的SARS-CoV-2病毒.机器学习 机器学习现象类型 现象类型预测 预后 预测 预测预言的意思是预言.风险因素 风险因素严重的SARS-CoV-2感染这是一个验证.验证 验证 验证 验证

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