Deep learning of pretreatment multiphase CT images for predicting response to lenvatinib and immune checkpoint inhibitors in unresectable hepatocellular carcinoma-Reference-Cited by-同舟云学术

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Deep learning of pretreatment multiphase CT images for predicting response to lenvatinib and immune checkpoint inhibitors in unresectable hepatocellular carcinoma

Published:2024-12 Issue: Volume:24 Page:247-257
ISSN:2001-0370
Container-title:Computational and Structural Biotechnology Journal
language:en
Short-container-title:Computational and Structural Biotechnology Journal

Author:

Liao Nan-Qing,Deng Zhu-Jian,Wei Wei,Lu Jia-Hui,Li Min-Jun,Ma Liang,Chen Qing-Feng,Zhong Jian-Hong

Funder

Specific Research Project of Guangxi for Research Bases and Talents

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference50 articles.

1. Phase Ib study of lenvatinib plus pembrolizumab in patients with unresectable hepatocellular carcinoma;Finn;J Clin Oncol,2020

2. Lenvatinib with or without immune checkpoint inhibitors for patients with unresectable hepatocellular carcinoma in real-world clinical practice;Chen;Cancer Immunol Immunother,2022

3. Evaluation and prediction of treatment response for hepatocellular carcinoma;Tsujita;Magn Reson Med Sci,2023

4. Predicting cancer outcomes with radiomics and artificial intelligence in radiology;Bera;Nat Rev Clin Oncol,2022

5. Development of a dual-energy spectral CT based nomogram for the preoperative discrimination of mutated and wild-type KRAS in patients with colorectal cancer;Cao;Clin Imaging,2021

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