Prediction of response to lenvatinib monotherapy for unresectable hepatocellular carcinoma by machine learning radiomics: A multicenter cohort study.
Zhiyuan BoBo ChenZhengxiao ZhaoQikuan HeYicheng MaoYunjun YangFei YaoYi YangZiyan ChenJinhuan YangHaitao YuJun MaLijun WuKaiyu ChenLuhui WangMingxun WangZhehao ShiXinfei YaoYulong DongXintong ShiYunfeng ShanZhengping YuYi WangGang ChenPublished in: Clinical cancer research : an official journal of the American Association for Cancer Research (2023)
Valuable ML radiomics models were constructed, with favorable performance in predicting the response to lenvatinib monotherapy for unresectable HCC.
Keyphrases
- machine learning
- locally advanced
- combination therapy
- lymph node metastasis
- liver metastases
- open label
- contrast enhanced
- wastewater treatment
- squamous cell carcinoma
- rectal cancer
- artificial intelligence
- magnetic resonance imaging
- randomized controlled trial
- clinical trial
- deep learning
- magnetic resonance
- computed tomography