Evidence map›Paper›PMID 41769373›Full record

ArticleToxicological research2026

Artificial intelligence‑based quantitative analysis of hepatic fibrosis in carbon tetrachloride-induced mouse model of metabolic dysfunction-associated steatohepatitis.

Jin-Hee Lee, Myung-Hwa Yang, Gyeongjin Han, Won Hoon Jung, Myung Ae Bae, Ji-Seok Han, Tae-Sung Koo, Jae-Woo Cho

Abstract read
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In one paragraph

Article in Toxicological research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Jin-Hee LeeCenter for Biomedical Diagnostic Research, Division of Next Generation Non-Clinical Research, Korea Institute of Toxicology (KIT), Daejeon, 34114 Republic of Korea.ORCID 0009-0007-7817-7614
Myung-Hwa YangCenter for Biomedical Diagnostic Research, Division of Next Generation Non-Clinical Research, Korea Institute of Toxicology (KIT), Daejeon, 34114 Republic of Korea.
Gyeongjin HanCenter for Biomedical Diagnostic Research, Division of Next Generation Non-Clinical Research, Korea Institute of Toxicology (KIT), Daejeon, 34114 Republic of Korea.
Won Hoon JungCenter for Rare Disease Therapeutic Technology, Therapeutics and Biotechnology Division, Korea Research Institute of Chemical Technology (KRICT), Daejeon, 34114 Republic of Korea.ORCID 0009-0008-4711-6453
Myung Ae BaeCenter for Rare Disease Therapeutic Technology, Therapeutics and Biotechnology Division, Korea Research Institute of Chemical Technology (KRICT), Daejeon, 34114 Republic of Korea.ORCID 0000-0002-2997-5018
Ji-Seok HanCenter for Biomedical Diagnostic Research, Division of Next Generation Non-Clinical Research, Korea Institute of Toxicology (KIT), Daejeon, 34114 Republic of Korea.
Tae-Sung KooGraduate School of New Drug Discovery and Development, Chungnam National University, Daejeon, 34134 Republic of Korea.ORCID 0000-0001-8046-6836
Jae-Woo ChoCenter for Biomedical Diagnostic Research, Division of Next Generation Non-Clinical Research, Korea Institute of Toxicology (KIT), Daejeon, 34114 Republic of Korea.ORCID 0000-0003-0072-7827

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liver fibrosis, a major histopathological indicator of chronic liver injury, is also a key feature of metabolic dysfunction-associated steatohepatitis. Its quantitative assessment in preclinical toxicology is frequently inconsistent and subjective. This study aimed to develop and validate multi-scale, patch-based convolutional neural network classification algorithms for automated fibrosis quantification in a carbon tetrachloride (CCl Graphical abstract: Supplementary Information: The online version contains supplementary material available at 10.1007/s43188-025-00326-8.

Indexed as

Automated quantificationDeep learningDigital pathologyHepatic fibrosisMetabolic dysfunction-associated steatohepatitis

Identifiers

PMID41769373
PMCPMC12945867

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.