Evidence map›Paper›PMID 35125095›Full record

ArticleBMC medical imaging2022

Dynamic chaotic gravitational search algorithm-based kinetic parameter estimation of hepatocellular carcinoma on

Jianfeng He, Tao Wang, Yongjin Li, Yinglei Deng, Shaobo Wang

Open access · goldAbstract read
In one paragraph

Article in BMC medical imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.4field-weighted citation impact, top 20% of its field
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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. KineticEJNMMI physics · 2024
    Article
  6. 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 at 1 institution in 1 country.

Jianfeng HeFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Yunnan Key Laboratory of Artificial Intelligence, Kunming, 650500, Yunnan, China.
Tao WangFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Yunnan Key Laboratory of Artificial Intelligence, Kunming, 650500, Yunnan, China.
Yongjin LiFaculty of Information Engineering and Automation, Kunming University of Science and Technology, Yunnan Key Laboratory of Artificial Intelligence, Kunming, 650500, Yunnan, China.
Yinglei DengPET/CT Center, Affiliated Hospital of Kunming University of Science and Technology, First People's Hospital of Yunnan, Kunming, 650031, China.
Shaobo WangPET/CT Center, Affiliated Hospital of Kunming University of Science and Technology, First People's Hospital of Yunnan, Kunming, 650031, China. wshbo_98@126.com.
Kunming University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKinetic parameters estimated with dynamic

methodsFive-minute dynamic PET/CT data of 20 HCCs were prospectively enrolled, and the kinetic parameters k

resultsThe results showed that there were significant differences between the HCCs and background liver tissues for k

conclusionsGSA enables accurate estimation of the kinetic parameters of dynamic PET/CT in the diagnosis of HCC, and DCGSA can enhance the diagnostic performance.

Indexed as

AlgorithmsCarcinoma, HepatocellularFemaleFluorodeoxyglucose F18HumansImage Processing, Computer-AssistedLiver NeoplasmsMalePositron Emission Tomography Computed TomographyRadiopharmaceuticalsFluorodeoxyglucose F18RadiopharmaceuticalsGravitational search algorithmHepatocellular carcinomaKinetic modelsPET/CT

Identifiers

PMID35125095
PMCPMC8818192
OpenAlexW4210419184

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.