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Updated: Jan 7, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
04:09

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

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[基于LASSO-proj算法的可解释神经网络框架用于华法林剂量预测的应用]

Chenlu Zhong1, Ye Zhu2, Xiang Gu2

  • 1Department of Cardiology, Gaoyou People's Hospital, Yangzhou, Jiangsu 225001, P. R. China.

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
|December 25, 2025
PubMed
概括

这项研究开发了一个可解释的机器学习模型来预测华法林剂量,提高了患者的安全性. 该模型准确地确定了用于个性化华法林治疗的VKORC1基因型,年龄和体重等关键因素.

关键词:
人工智能的人工智能是人工智能.深度学习是一种深度学习.剂量预测的预测沃尔法林的战争

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