ReviewZhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology2025
[Clinical practice and challenges from simple models to precise integration for serological evaluation of a non-invasive diagnosis of liver fibrosis].
Review in Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
4 authors.
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Abstract
Liver fibrosis is a key pathological process in the progression of chronic liver disease, and its early stage and accurate diagnosis are crucial for improving patient prognosis. In recent years, the non-invasive diagnosis of liver fibrosis has gradually shifted from the traditional model based on conventional serological indicators to an evaluation system that integrates new biomarkers and multi-omics technologies. This article systematically reviews the evolution of the serological evaluation system for non-invasive diagnosis of liver fibrosis, introduces the application progress of serological models, novel biomarkers, and the introduction of multimodal integration and artificial intelligence technology, and analyzes their advantages and limitations, with aim of providing novel ideas for achieving accurate diagnosis and assisting in clinical management of patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.