Evidence map›Paper›PMID 36688019›Full record

ReviewWorld journal of gastroenterology2023

Artificial intelligence and inflammatory bowel disease: Where are we going?

Leonardo Da Rio, Marco Spadaccini, Tommaso Lorenzo Parigi, Roberto Gabbiadini, Arianna Dal Buono, Anita Busacca, Roberta Maselli, Alessandro Fugazza, Matteo Colombo, Silvia Carrara and 6 more

Open access · hybridAbstract readReview
In one paragraph

Review in World journal of gastroenterology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 1 pooled it
19.7field-weighted citation impact, top 1% 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

48 citing papers in PubMed, 1 synthesis or guideline pooled it, 63 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Review
  11. Artificial intelligence in the management of inflammatory bowel disease: What's next?World journal of gastrointestinal pharmacology and therapeutics · 2026
    Review
  12. Article
  13. Review
  14. Article
  15. Review
  16. Review
  17. Article
  18. Review
  19. Integrative Analysis of Intestinal Transcriptomes UnderscoresBioinformatics and biology insights · 2026
    Article
  20. 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

16 authors at 3 institutions in 1 country.

Leonardo Da RioDepartment of Endoscopy, Humanitas Research Hospital, IRCCS, Rozzano 20089, Milano, Italy.
Marco SpadacciniDepartment of Biomedical Sciences, Humanitas University, Rozzano 20089, Milano, Italy.
Tommaso Lorenzo ParigiDepartment of Biomedical Sciences, Humanitas University, Rozzano 20089, Milano, Italy.
Roberto GabbiadiniIBD Center, Humanitas Research Hospital, IRCCS, Rozzano 20089, Milano, Italy.
Arianna Dal BuonoIBD Center, Humanitas Research Hospital, IRCCS, Rozzano 20089, Milano, Italy.
Anita BusaccaIBD Center, Humanitas Research Hospital, IRCCS, Rozzano 20089, Milano, Italy.
Roberta MaselliDepartment of Endoscopy, Humanitas Research Hospital, IRCCS, Rozzano 20089, Milano, Italy.
Alessandro FugazzaDepartment of Endoscopy, Humanitas Research Hospital, IRCCS, Rozzano 20089, Milano, Italy.
Matteo ColomboDepartment of Endoscopy, Humanitas Research Hospital, IRCCS, Rozzano 20089, Milano, Italy.
Silvia CarraraDepartment of Endoscopy, Humanitas Research Hospital, IRCCS, Rozzano 20089, Milano, Italy.
Gianluca FranchellucciDepartment of Endoscopy, Humanitas Research Hospital, IRCCS, Rozzano 20089, Milano, Italy.
Ludovico AlfaroneDepartment of Endoscopy, Humanitas Research Hospital, IRCCS, Rozzano 20089, Milano, Italy.
Antonio FacciorussoGastroenterology Unit, Department of Medical Sciences, University of Foggia, Foggia 71122, Foggia, Italy.
Cesare HassanDepartment of Endoscopy, Humanitas Research Hospital, IRCCS, Rozzano 20089, Milano, Italy.
Alessandro RepiciDepartment of Endoscopy, Humanitas Research Hospital, IRCCS, Rozzano 20089, Milano, Italy.
Alessandro ArmuzziIBD Center, Humanitas Research Hospital, IRCCS, Rozzano 20089, Milano, Italy.
Humanitas University · ITIRCCS Humanitas Research Hospital · ITUniversity of Foggia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inflammatory bowel diseases, namely ulcerative colitis and Crohn's disease, are chronic and relapsing conditions that pose a growing burden on healthcare systems worldwide. Because of their complex and partly unknown etiology and pathogenesis, the management of ulcerative colitis and Crohn's disease can prove challenging not only from a clinical point of view but also for resource optimization. Artificial intelligence, an umbrella term that encompasses any cognitive function developed by machines for learning or problem solving, and its subsets machine learning and deep learning are becoming ever more essential tools with a plethora of applications in most medical specialties. In this regard gastroenterology is no exception, and due to the importance of endoscopy and imaging numerous clinical studies have been gradually highlighting the relevant role that artificial intelligence has in inflammatory bowel diseases as well. The aim of this review was to summarize the most recent evidence on the use of artificial intelligence in inflammatory bowel diseases in various contexts such as diagnosis, follow-up, treatment, prognosis, cancer surveillance, data collection, and analysis. Moreover, insights into the potential further developments in this field and their effects on future clinical practice were discussed.

Indexed as

Colitis, UlcerativeCrohn DiseaseInflammatory Bowel DiseasesArtificial IntelligenceHumansPrognosisArtificial intelligenceComputer-aided diagnosisCrohn’s diseaseInflammatory bowel diseaseMachine learningUlcerative colitis

Identifiers

PMID36688019
PMCPMC9850939
OpenAlexW4315651387

What Socratic 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 Socratic graph.