Work

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

Year: 2025

Type: article

Abstract: • The lipids fingerprint profile from the inflammation to cancer in HCC was provided. • Applying ML and explainable DL to analyze multi-omics data showed great potential. • 12 lipid biomarkers associated with “inflammatory-cancer” transition were identified. • A robust diagnostic model was developed for predicting HCC progression.

Source: Journal of Pharmaceutical Analysis

DOI: 10.1016/j.jpha.2025.101253

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

Institutions: Shenyang Pharmaceutical University, Kanion Pharmaceutical (China)

Language: English

Topic: Metabolomics and Mass Spectrometry Studies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,950

Funders: National Natural Science Foundation of China, Natural Science Foundation of Liaoning Province, Department of Education of Liaoning Province, Key Research and Development Program of Liaoning Province

Awards: G1662676816, G4072303032, G508351589

OpenAlex ID: W4408076872

FWCI: 1.821

Cites: 5

Cited by: 7

Related to: 10