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

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

Objectives: Combination therapy of lenvatinib and immune checkpoint inhibitors (CLICI) has emerged as a promising approach for managing unresectable hepatocellular carcinoma (HCC). However, the response to such treatment is observed in only a subset of patients, underscoring the pressing need for re...

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Podrobná bibliografie
Hlavní autoři: Nan-Qing Liao, Zhu-Jian Deng, Wei Wei, Jia-Hui Lu, Min-Jun Li, Liang Ma, Qing-Feng Chen, Jian-Hong Zhong
Médium: Článek
Jazyk:English
Vydáno: Elsevier 2024-12-01
Edice:Computational and Structural Biotechnology Journal
Témata:
Deep learning
Hepatocellular carcinoma
Immune checkpoint inhibitors
Lenvatinib
Multiphase computerized tomography
On-line přístup:http://www.sciencedirect.com/science/article/pii/S2001037024000849

Internet

http://www.sciencedirect.com/science/article/pii/S2001037024000849

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