Evidence map›Paper›PMID 40419365›Full record

ReviewZhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology2025

[New progress in the technology of non-invasive diagnosis for small hepatocellular carcinoma].

S X Zhao, Z A Zhang, Y M Nan

Abstract readReviewEnglish Abstract
PubMed Full text at PMC Publisher
In one paragraph

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. [Advances and challenges in new technologies for imaging evaluation of liver fibrosis].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

S X ZhaoDepartment of Traditional and Western Medical Hepatology, Department of Gastroenterology, Hebei Medical University Third Hospital, Shijiazhuang 050051, China Hebei Provincial Key Laboratory of Liver Fibrosis Mechanism Study in Chronic Liver Diseases, Hebei International Joint Research Center for Liver Cancer Molecular Diagnosis, Hebei International Science and Technology Cooperation Base, Shijiazhuang 050051, China.
Z A ZhangDepartment of Traditional and Western Medical Hepatology, Department of Gastroenterology, Hebei Medical University Third Hospital, Shijiazhuang 050051, China Hebei Provincial Key Laboratory of Liver Fibrosis Mechanism Study in Chronic Liver Diseases, Hebei International Joint Research Center for Liver Cancer Molecular Diagnosis, Hebei International Science and Technology Cooperation Base, Shijiazhuang 050051, China.
Y M NanDepartment of Traditional and Western Medical Hepatology, Department of Gastroenterology, Hebei Medical University Third Hospital, Shijiazhuang 050051, China Hebei Provincial Key Laboratory of Liver Fibrosis Mechanism Study in Chronic Liver Diseases, Hebei International Joint Research Center for Liver Cancer Molecular Diagnosis, Hebei International Science and Technology Cooperation Base, Shijiazhuang 050051, China.

Funding

Hebei Province Medical Application Technology Tracking Project GZ2024048Key Research and Development Plan Projects of Hebei Province 23377705Dthe Introduction of Foreign Intelligence Program in Hebei Province 2024
6 · The paper itself

Abstract

The diagnosis of small liver cancer is crucial to improving the survival rate of patients. However, traditional diagnostic methods are highly invasive, so the development of non-invasive diagnostic techniques is particularly important. In recent years, non-invasive diagnostic techniques have shown good prospects in the early-stage detection of liver cancer. Therefore, current research focuses on biomarkers, imaging technologies, and artificial intelligence applications. This article aims to review the latest advances in non-invasive diagnostic technologies, discuss their advantages and challenges in clinical application, and look forward to future research directions so as to provide a reference for further improving the diagnosis rate of small liver cancer.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsArtificial IntelligenceBiomarkers, TumorDiagnostic ImagingEarly Detection of CancerHumansMagnetic Resonance ImagingTomography, X-Ray ComputedBiomarkers, Tumor

Identifiers

PMID40419365
PMCPMC12677291

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.