Evidence mapPaperPMID 41368307Full record

ReviewFrontiers in medicine2025

Liver biopsy in the modern era: from traditional techniques to artificial intelligence and multi-omics integration.

Nasar Alwahaibi, Maryam Alwahaibi

Abstract readReview
In one paragraph

Review in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

2 authors.

Nasar AlwahaibiDepartment of Biomedical Science, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Oman.
Maryam AlwahaibiDepartment of Biomedical Science, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Oman.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liver biopsy remains a cornerstone in the diagnosis and management of various hepatic disorders. This mini-review provides a concise overview of traditional liver biopsy techniques, percutaneous, plugged, transjugular, and laparoscopic, highlighting their clinical indications, histopathological evaluation, and limitations. The review also explores recent advancements, including the integration of artificial intelligence in imaging modalities such as ultrasound, MRI, and CT, as well as its emerging role in histopathological analysis, particularly for assessing fibrosis, steatosis, inflammation, and cancer. In parallel, the application of multi-omics technologies is discussed as a promising complement to histology, offering molecular-level insights into disease progression and therapeutic response. Despite these technological steps, there remains a gap in the literature regarding how traditional biopsy methods are being effectively integrated with these emerging tools, and how liver biopsy continues to retain its clinical relevance in the era of artificial intelligence and multi-omics approaches. This review underscores the evolving landscape of liver biopsy and calls for harmonized frameworks that combine conventional techniques with digital innovations to enhance diagnostic accuracy, standardization, and patient care.

Indexed as

artificial intelligencedigital pathologyhepatologyhistological quantificationliver biopsymulti-omics

Identifiers

PMID41368307
PMCPMC12682794

What Socratic holds

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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.