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实用的机器学习模型,用于在扩散性血管内凝血进展到明显阶段之前,对其进行早期和准确的预测

Yutaka Umemura1,2, Masataka Fujimoto3,4, Takahiro Kinoshita4

  • 1Division of Trauma and Surgical Critical Care, Osaka General Medical Center, Osaka, Japan.

Thrombosis and haemostasis
|February 10, 2026
PubMed
概括

机器学习模型准确地预测了毒症患者早期的明显传播性血管内凝血 (DIC). 这使得在明显的DIC发展之前,可以及时进行抗凝剂治疗,从而改善患者的治疗结果.

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