Evidence map›Paper›PMID 36604292›Full record

ReviewSeminars in perinatology2023

Biomarkers of necrotizing enterocolitis in the era of machine learning and omics.

Tyler Leiva, Shiloh Lueschow, Kathryn Burge, Christa Devette, Steven McElroy, Hala Chaaban

Abstract readReview
In one paragraph

Review in Seminars in perinatology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
  4. [Recent advances in artificial intelligence for auxiliary diagnosis and management of neonatal necrotizing enterocolitis].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2025
    Review
  5. Article
  6. Necrotizing Enterocolitis: What's New and What's Next?International journal of molecular sciences · 2025
    Review
  7. Present and future of microbiome-targeting therapeutics.The Journal of clinical investigation · 2025
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. 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

6 authors.

Tyler LeivaDepartment of Surgery, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA.
Shiloh LueschowDepartment of Microbiology and Immunology, Stead Family Department of Pediatrics, University of Iowa, Iowa City, IA, USA.
Kathryn BurgeDepartment of Pediatrics, The University of Oklahoma Health Sciences Center, 1200 N. Everett Dr., ETNP 7504, Oklahoma City, OK 73104, USA.
Christa DevetteDepartment of Pediatrics, The University of Oklahoma Health Sciences Center, 1200 N. Everett Dr., ETNP 7504, Oklahoma City, OK 73104, USA.
Steven McElroyDepartment of Pediatrics, University of California Davis, Sacramento, CA, USA.
Hala ChaabanDepartment of Pediatrics, The University of Oklahoma Health Sciences Center, 1200 N. Everett Dr., ETNP 7504, Oklahoma City, OK 73104, USA. Electronic address: hala-chaaban@ouhsc.edu.

Funding

Vascular-macrophage crosstalk in GBM immunosuppressionP20GM134973 · NIGMS · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI Sree Deepthi Muthukrishnan · 2020 to 2026
$17.6M
Effect of fetal exposure to maternal inflammation on offspring Paneth cell development and homeostasisR01DK125415 · NIDDK · UNIVERSITY OF CALIFORNIA AT DAVIS · PI MCELROY, STEVEN JAMES · 2021 to 2025
$2.5M
NIDDK NIH HHS R01 DK125415NIGMS NIH HHS P20 GM134973
6 · The paper itself

Abstract

Necrotizing enterocolitis (NEC) continues to be a major cause of morbidity and mortality in preterm infants. Despite decades of research in NEC, no reliable biomarkers can accurately diagnose NEC or predict patient prognosis. The recent emergence of multi-omics could potentially shift NEC biomarker discovery, particularly when evaluated using systems biology techniques. Furthermore, the use of machine learning and artificial intelligence in analyzing this 'big data' could enable novel interpretations of NEC subtypes, disease progression, and potential therapeutic targets, allowing for integration with personalized medicine approaches. In this review, we evaluate studies using omics technologies and machine learning in the diagnosis of NEC. Future implications and challenges inherent to the field are also discussed.

Indexed as

Enterocolitis, NecrotizingInfant, Newborn, DiseasesArtificial IntelligenceBiomarkersHumansInfantInfant, NewbornInfant, PrematureMachine LearningBiomarkers

Identifiers

PMID36604292
PMCPMC9975050

What OpenQuestion 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 OpenQuestion graph.