Evidence map›Paper›PMID 39714118›Full record

ReviewThe Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology2024

Harnessing the Power of AI for Enhanced Diagnosis and Treatment of Hepatocellular Carcinoma.

Ting Jin, Mengchen Luo, Feng Chen, Jin Bai, Jin Ding

Abstract readReview
In one paragraph

Review in The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Prediction of Histopathological Grade of Hepatocellular Carcinoma by Gadoxetic Acid-Enhanced Magnetic Resonance Imaging Radiomics Features.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2025
    Article
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

5 authors.

Ting JinDepartment of Gastroenterology, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, Zhejiang, China.
Mengchen LuoDepartment of Gastroenterology, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, Zhejiang, China.
Feng ChenDepartment of Gastroenterology, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, Zhejiang, China.
Jin BaiCancer Institute, Xuzhou Medical University, Xuzhou, Jiangsu, China.
Jin DingDepartment of Gastroenterology, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since its advent, artificial intelligence (AI) has been continuously researched, and substantial progress has been made in many fields, such as the diagnosis and therapies for cancer. Due to the advantages of high efficiency, rapidity, and precision, AI has been increasingly adopted in the medical field to improve patient prognosis and the efficiency of medical procedures. Thus, AI technology has become a powerful driving force and support mechanism in the medical and health industry. Hepatocellular carcinoma (HCC) is the sixth most common cancer and the fourth leading cause of cancer mortality worldwide, with a 5-year relative survival rate of 18%. The early diagnosis and postsurgical treatment of HCC are key factors related to its prognosis, which provides an opportunity for the application of AI in HCC diagnosis and treatment. This review will summarize the application of AI in the diagnosis and treatment of HCC to provide prospects for deeper and wider applications.

Indexed as

Artificial IntelligenceCarcinoma, HepatocellularLiver NeoplasmsEarly Detection of CancerHumansPrognosisdiagnosishepatocellular carcinomainternet medicinertificial intelligencetreatment

Identifiers

PMID39714118
PMCPMC12001482

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.