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Updated: Jun 8, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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使用成年住院患者数据的自主监督机器学习可以为儿科临床预测任务产生有效的模型

Joshua Lemmon1, Lin Lawrence Guo1, Ethan Steinberg2

  • 1Program in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON M5G1X8, Canada.

Journal of the American Medical Informatics Association : JAMIA
|August 28, 2023
PubMed
概括

在成年患者数据上训练的自主监督学习模型证明与儿科临床预测的传统模型无差. 这种方法可以提高儿科电子健康记录 (EHR) 模型的开发,而不需要广泛的再培训.

关键词:
电子健康记录是电子健康记录.基础模型的基础模型.机器学习是机器学习.模型的稳定性 模型的稳定性自主监督学习学习转移学习转移学习

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相关概念视频

Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis: