Digital biopsy for liver diseases： A review of technological advances and application prospects

Yang ZHOU; Zhenwei CHEN; Hanying SHI; Kongying LIN; Yingchao WANG; Yongyi ZENG

doi:10.12449/JCH251102

Volume 41 Issue 11

Nov. 2025

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Article Navigation > Journal of Clinical Hepatology > 2025 > 41(11): 2207-2212

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Digital biopsy for liver diseases： A review of technological advances and application prospects

DOI: 10.12449/JCH251102

1.
a. Biological Information Biobank，Mengchao Hepatobiliary Hospital of Fujian Medical University，Fuzhou 350025，China
2.
Department of Information Technology，Mengchao Hepatobiliary Hospital of Fujian Medical University，Fuzhou 350025，China
3.
Office of Teaching Affairs，Mengchao Hepatobiliary Hospital of Fujian Medical University，Fuzhou 350025，China
4.
Department of Hepatopancreatobiliary Surgery，Mengchao Hepatobiliary Hospital of Fujian Medical University，Fuzhou 350025，China
5.
Liver Disease Research Center of Fujian Province，Fuzhou 350025，China

Research funding:

National Natural Science Foundation of China (62275050);

National Key Research and Development Program of China (2022YFC2407304);

Natural Science Foundation of Fujian Province (2025J011318);

Fuzhou Science and Technology Program (2024-G-015)

More Information

Corresponding author: ZENG Yongyi， lamp197311@126.com （ORCID： 0000-0001-8823-698X）
Received Date: 2025-09-01
Accepted Date: 2025-10-18
Published Date: 2025-11-25

Abstract

Abstract

Digital biopsy for liver diseases is characterized by the deep integration of artificial intelligence （AI） technologies and large-scale liver disease data， through which intelligent analytics are applied to support clinical decision-making and full-cycle management. This article reviews the AI technical framework based on standardized data governance and centered on multimodal large medical models， covering the application of natural language processing， knowledge map， generative AI， and large language models in the establishment of databases for specialty diseases， diagnosis， prognosis prediction， treatment， and automated medical documentation. This article also discusses the application prospects of this framework in medical education， scientific research， and healthcare management. Although this technique shows broad application potential， it still faces challenges in areas such as multi-center data integration， model interpretability， ethics， and data security. In the future， a smart ecosystem with closed-loop optimization and human-AI collaboration should be established to promote the comprehensive implementation of digital biopsy in the whole process of medicine， education， research， and management， thereby providing help for the precise prevention and control and holistic health management of liver diseases.
- Liver Disease Digital Biopsy Platform,
- Artificial Intelligence,
- Databases

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References(50)

References

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Digital biopsy for liver diseases： A review of technological advances and application prospects

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