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Updated: Jun 15, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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使用域调整和诱导转移学习来改善重症监护室患者结果预测:回顾性观察性研究

Maruthi Kumar Mutnuri1,2, Henry Thomas Stelfox3,4, Nils Daniel Forkert5,6

  • 1Data Intelligence for Health Lab, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.

Journal of medical Internet research
|August 21, 2024
PubMed
概括

转移学习 (TL) 显著改善了重症监护室 (ICU) 患者的预测结果,特别是在数据稀缺的情况下. 诱导转移学习 (ITL) 模型表现出优于域适应 (DA) 和基线模型的性能.

关键词:
深度学习是一种深度学习.电子健康记录 电子健康记录重症监护室的重症监护室是重症监护室的重症监护室.预测患者的结果,预测患者的结果.转移学习转移学习

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Critical attributes of NCIS include:
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The treatment for acute respiratory failure varies based on factors like the underlying cause, overall health, and severity. A collaborative healthcare team is essential for early detection, often through arterial blood gas analysis. Identifying the cause is the primary goal, with treatment strategies adjusted for ventilation/perfusion (V/Q) mismatch, shunting, or diffusion impairment.
Ensure that patients are monitored continuously for their response to therapy, including changes in...
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