An interpretable machine learning model using routine clinical data for early recurrence prediction in hepatocellular carcinoma

Ding-Fan Guo; Qi Wen; Xiang Zhang; Jian Luo; Lin-Wei Fan; Yun-Hui Liang; Qi Feng; Ting Wang; Kun-He Zhang

doi:10.1038/s41598-026-38484-w

An interpretable machine learning model using routine clinical data for early recurrence prediction in hepatocellular carcinoma

D Ding-Fan Guo Q Qi Wen (Shaanxi Key Laboratory of Macromolecular Science and Technology, Xi’an Key Laboratory of Hybrid Luminescent Materials and Photonic Device, MOE Key Laboratory of Material Physics and Chemistry under Extraordinary Conditions, School of Chemistry and Chemical Engineering) X Xiang Zhang J Jian Luo L Lin-Wei Fan Y Yun-Hui Liang Q Qi Feng T Ting Wang (Department of Radiation Oncology The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital Zhengzhou China) K Kun-He Zhang

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Article Details

Journal Scientific Reports

Volume / Issue Vol. 16, Issue 1

Published February 05, 2026

DOI 10.1038/s41598-026-38484-w

ISSN 2045-2322

Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (9)

D

Ding-Fan Guo

Q

Qi Wen

Shaanxi Key Laboratory of Macromolecular Science and Technology, Xi’an Key Laboratory of Hybrid Luminescent Materials and Photonic Device, MOE Key Laboratory of Material Physics and Chemistry under Extraordinary Conditions, School of Chemistry and Chemical Engineering

X

Xiang Zhang

J

Jian Luo

L

Lin-Wei Fan

Y

Yun-Hui Liang

Q

Qi Feng

T

Ting Wang

Department of Radiation Oncology The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital Zhengzhou China

K

Kun-He Zhang

An interpretable machine learning model using routine clinical data for early recurrence prediction in hepatocellular carcinoma

Article Details

Journal Info

Authors (9)

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