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将可解释的深度学习与多组学相结合,用于筛选涵盖“炎症-癌症”转变的肝细胞癌进展性诊断生物标志物。

Integrating explainable deep learning with multi-omics for screening progressive diagnostic biomarkers of hepatocellular carcinoma covering the "inflammation-cancer" transformation.

作者信息

Li Saiyu, Zhang Yiwen, Guan Lifang, Dong Yijing, Zhang Mingzhe, Zhang Qian, Xu Huarong, Xiao Wei, Wang Zhenzhong, Cui Yan, Li Qing

机构信息

School of Pharmacy, Shenyang Pharmaceutical University, Shenyang, 110016, China.

State Key Laboratory of New-tech for Chinese Medicine Pharmaceutical Process, Jiangsu Kanion Pharmaceutical Co., Ltd., Lianyungang, 222001, China.

出版信息

J Pharm Anal. 2025 Sep;15(9):101253. doi: 10.1016/j.jpha.2025.101253. Epub 2025 Mar 1.

DOI:10.1016/j.jpha.2025.101253
PMID:40919103
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12410188/
Abstract

Image 1.

摘要

图1。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b13a/12410188/07d41ac83478/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b13a/12410188/990f968cf678/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b13a/12410188/07d41ac83478/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b13a/12410188/990f968cf678/ga1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b13a/12410188/07d41ac83478/gr1.jpg

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本文引用的文献

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Hepatology. 2025 Jan 1;81(1):168-180. doi: 10.1097/HEP.0000000000000879. Epub 2024 Apr 17.
2
Machine learning of plasma metabolome identifies biomarker panels for metabolic syndrome: findings from the China Suboptimal Health Cohort.基于血浆代谢组学的机器学习方法鉴定出代谢综合征的生物标志物组合:来自中国亚健康队列研究的发现。
Cardiovasc Diabetol. 2022 Dec 23;21(1):288. doi: 10.1186/s12933-022-01716-0.
3
Integrative omics analysis identifies biomarkers of idiopathic pulmonary fibrosis.
综合组学分析鉴定特发性肺纤维化的生物标志物。
Cell Mol Life Sci. 2022 Jan 11;79(1):66. doi: 10.1007/s00018-021-04094-0.
4
Hepatocellular carcinoma (HCC): Epidemiology, etiology and molecular classification.肝细胞癌(HCC):流行病学、病因学和分子分类。
Adv Cancer Res. 2021;149:1-61. doi: 10.1016/bs.acr.2020.10.001. Epub 2020 Nov 28.
5
Development and Validation of a Deep Learning Model for Non-Small Cell Lung Cancer Survival.深度学习模型在非小细胞肺癌生存预测中的建立与验证。
JAMA Netw Open. 2020 Jun 1;3(6):e205842. doi: 10.1001/jamanetworkopen.2020.5842.