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Updated: Jun 24, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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一个机器学习的案例研究,以预测罕见的临床事件的兴趣:不平衡的数据,可解释性,和实际考虑

Sheng Zhong1, Jane Zhang1, Jenny Jiao1

  • 1Data and Statistical Sciences, AbbVie Inc., North Chicago, Illinois, USA.

Journal of biopharmaceutical statistics
|June 11, 2024
PubMed
概括

本研究提出了一种机器学习框架,用于预测药物开发中的罕见临床事件. 它通过早期检测和风险因素识别来提高患者的安全性.

关键词:
增强的提升 提高的提升这是分类分类的分类.不平衡的数据不平衡的数据.机器学习是机器学习.模型的解释性可解释性

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