Unsupervised Machine Learning of MRI Radiomics Features Identifies Two Distinct Subgroups with Different Liver Function Reserve and Risks of Post-Hepatectomy Liver Failure in Patients with Hepatocellular Carcinoma.

Qiang Wang,Changfeng Li,Geng Chen,Kai Feng,Zhiyu Chen,Feng Xia,Ping Cai,Leida Zhang,Ernesto Sparrelid,Torkel B Brismar,Kuansheng Ma

Cancers（2023）

引用 0|浏览23

暂无评分

摘要

Based on the radiomics features of gadoxetic-acid-enhanced MRI, unsupervised clustering analysis identified two distinct subgroups with different liver function reserves and risks of PHLF in HCC patients. Future studies are required to validate our findings.

查看译文

关键词

radiomics, magnetic resonance imaging, machine learning, liver function, hepatocellular carcinoma

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要