Evidence map›Paper›PMID 39267561›Full record

ReviewZhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology2024

[Research progress of radiomics in hepatocellular carcinoma].

X M Li, Z Y Liu

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, 2024. 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. 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

2 authors.

X M LiDepartment of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou 510280, China.
Z Y LiuDepartment of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application, Guangzhou 510080, China.

Funding

Guangdong Province Science and Technology Plan Project 2022B1212010011National Key Research and Development Program of China 2021YFF1201003National Natural Science Foundation of China 82302315
6 · The paper itself

Abstract

Primary liver cancer is a common malignant digestive system tumor, with hepatocellular carcinoma being the most common pathological type. Radiomics significantly boosts the efficiency of predictions by accurately capturing the intrinsically heterogeneous features of tumors that are difficult to discern with the human eye in imaging images. This article outlines the background and concepts of radiomics, introduces its latest research progress in various aspects, such as diagnosis and differential diagnosis, prediction of pathological molecular subtypes, efficacy evaluation, and survival prediction, and further discusses its limitations and prospects in HCC.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsDiagnosis, DifferentialHumansMagnetic Resonance ImagingRadiomicsTomography, X-Ray Computed

Identifiers

PMID39267561
PMCPMC12898878

What OpenQuestion holds

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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 OpenQuestion graph.