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一种深度学习方法,可以预测长期接受抗凝治疗的患者随时间推移的出血风险

Soroush Shahryari Fard1, Theodore J Perkins2, Philip S Wells1

  • 1The Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, Ontario, Canada; Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada.

Journal of thrombosis and haemostasis : JTH
|April 20, 2024
PubMed
概括

使用患者随访数据的深度学习模型显著改善了接受抗凝治疗的患者的大型出血预测. 这种方法解释了不断变化的临床变化,增强了风险分层,超出了基线预测因素.

关键词:
临床决策规则 临床决策规则计算神经网络是一种计算神经网络.深度学习是一种深度学习.监督机器学习是指监督机器学习.静脉血栓塞栓症是一种静脉血栓塞栓.

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Hemostasis is a crucial process that prevents excessive blood loss from damaged blood vessels. It involves various mechanisms such as vasoconstriction, platelet adhesion and activation, and fibrin formation. The importance of each mechanism depends on the type of vessel injury. In contrast, thrombosis is the abnormal formation of a blood clot within the blood vessels, leading to potential complications if the clot obstructs blood flow. Thrombosis can be caused by increased coagulability of the...
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Hemostasis, the process that stops bleeding after a blood vessel injury, is crucial for maintaining the integrity of the circulatory system. However, disorders of hemostasis can disrupt this delicate balance, leading to either excessive clotting or bleeding. These disorders can be broadly classified into thromboembolic disorders and bleeding disorders.
Thromboembolic Disorders
Two factors primarily cause thromboembolic conditions.
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