ArticleWorld journal of gastroenterology2022
Comments on validation of conventional non-invasive fibrosis scoring systems in patients with metabolic associated fatty liver disease.
Article in World journal of gastroenterology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed, 1 citations in OpenAlex.
- Development and validation of a machine learning model for identifying liver fibrosis in MAFLD: a retrospective model development study.BMC medical informatics and decision making · 2026Article
- Article
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To evaluate and predict liver fibrosis in patients with nonalcoholic fatty liver disease (NAFLD), several non-invasive scoring systems were built and widely used in the progress of diagnosis and treatment, which showed great diagnostic efficiency, such as aspartate aminotransferase to platelet ratio index, fibrosis-4 index, body mass index, aspartate aminotransferase to alanine aminotransferase ratio, diabetes score and NAFLD fibrosis score. Since the new concept of metabolic associated fatty liver disease (MAFLD) was proposed, the clinical application value of the non-invasive scoring systems mentioned above has not been assessed in MAFLD. The evaluation of the diagnostic performance of these non-invasive scoring systems will provide references for clinicians in the diagnosis of MAFLD.
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