Evidence map›Paper›PMID 39435049›Full record

ReviewTherapeutic advances in gastroenterology2024

AI and endoscopy/histology in UC: the rise of machine.

Olga Maria Nardone, Yasuharu Maeda, Marietta Iacucci

Abstract readReview
In one paragraph

Review in Therapeutic advances in gastroenterology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

3 authors.

Olga Maria NardoneDivision of Gastroenterology, Department of Public Health, University Federico II of Naples, Naples, Italy.ORCID https://orcid.org/0000-0002-9554-4785
Yasuharu MaedaAPC Microbiome Ireland, College of Medicine and Health, University College Cork, Cork, Ireland.
Marietta IacucciMercy/Cork University Hospitals, Room 1.07, Clinical Sciences Building, Cork, Ireland.ORCID https://orcid.org/0000-0002-3142-9550

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The gap between endoscopy and histology is getting closer with the introduction of sophisticated endoscopic technologies. Furthermore, unprecedented advances in artificial intelligence (AI) have enabled objective assessment of endoscopy and digital pathology, providing accurate, consistent, and reproducible evaluations of endoscopic appearance and histologic activity. These advancements result in improved disease management by predicting treatment response and long-term outcomes. AI will also support endoscopy in raising the standard of clinical trial study design by facilitating patient recruitment and improving the validity of endoscopic readings and endoscopy quality, thus overcoming the subjective variability in scoring. Accordingly, AI will be an ideal adjunct tool for enhancing, complementing, and improving our understanding of ulcerative colitis course. This review explores promising AI applications enabled by endoscopy and histology techniques. We further discuss future directions, envisioning a bright future where AI technology extends the frontiers beyond human limits and boundaries.

Indexed as

artificial intelligencecomputer-aided diagnosisconvolutional neural networkdigital pathologyendo-histologic mucosal healingmachine learningulcerative colitis

Identifiers

PMID39435049
PMCPMC11491880

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.