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Updated: Jul 2, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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在2型糖尿病中探索甲胺单疗反应:通过使用机器学习算法的临床,基因组和蛋白质组标记器进行计算洞察

Angelina Thomas Villikudathil1, Declan H Mc Guigan1, Andrew English2

  • 1Ulster University, Centre for Stratified Medicine, Faculty of Life and Health Sciences, Magee Campus, Londonderry, Northern Ireland, United Kingdom.

Computers in biology and medicine
|February 18, 2024
PubMed
概括

这项研究确定了临床,基因组和蛋白质组生物标志物,以预测2型糖尿病患者对甲福明的反应. 一个机器学习模型在早期识别非响应者方面取得了83%的准确性.

关键词:
发现生物标志物的发现.波鲁塔 (Boruta) 是一个波鲁塔 (Boruta)临床数据分析临床数据分析基因组学就是基因组学.机器学习是机器学习.梅特福林的治疗方法.蛋白质组学是指蛋白质组学.单个核酸的多态性.2 型糖尿病 2 型糖尿病

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