Evidence map›Paper›PMID 37512529›Full record

ArticleMetabolites2023

Exploring the Potential Performance of Fibroscan for Predicting and Evaluating Metabolic Syndrome using a Feature Selected Strategy of Machine Learning.

Kuan-Lin Chiu, Yu-Da Chen, Sen-Te Wang, Tzu-Hao Chang, Jenny L Wu, Chun-Ming Shih, Cheng-Sheng Yu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Metabolites, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
0.2field-weighted citation impact, top 43% 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 1 citations in OpenAlex.

  1. Pooled it
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

7 authors at 2 institutions in 1 country.

Kuan-Lin ChiuDepartment of Family Medicine, Taipei Medical University Hospital, Taipei 110301, Taiwan.
Yu-Da ChenDepartment of Family Medicine, Taipei Medical University Hospital, Taipei 110301, Taiwan.
Sen-Te WangDepartment of Family Medicine, Taipei Medical University Hospital, Taipei 110301, Taiwan.
Tzu-Hao ChangGraduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 235603, Taiwan.ORCID 0000-0001-7011-3754
Jenny L WuGraduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei 235603, Taiwan.
Chun-Ming ShihDepartment of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan.
Cheng-Sheng YuGraduate Institute of Data Science, College of Management, Taipei Medical University, Taipei 235603, Taiwan.ORCID 0000-0002-3334-0816
Taipei Medical University Hospital · TWTaipei Medical University · TW

Funding

Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan DP2-111-21121-01-A-10National Science and Technology Council (Taiwan) NSTC111-2314-B-038-163
6 · The paper itself

Abstract

Metabolic syndrome (MetS) includes several conditions that can increase an individual's predisposition to high-risk cardiovascular events, morbidity, and mortality. Non-alcoholic fatty liver disease (NAFLD) is a predominant cause of cirrhosis, which is a global indicator of liver transplantation and is considered the hepatic manifestation of MetS. FibroScan

Indexed as

controlled attenuation parameterliver steatosisliver stiffness measurementmachine learningmetabolic syndromenon-alcoholic fatty liver disease

Identifiers

PMID37512529
PMCPMC10383149
OpenAlexW4383375873

What Socratic 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 Socratic graph.