Evidence map›Paper›PMID 39220079›Full record

ArticleWorld journal of gastrointestinal surgery2024

Machine learning in predicting postoperative complications in Crohn's disease.

Li-Fan Zhang, Liu-Xiang Chen, Wen-Juan Yang, Bing Hu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in World journal of gastrointestinal surgery, 2024. 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

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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

4 authors.

Li-Fan ZhangDepartment of Gastroenterology and Hepatology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China.
Liu-Xiang ChenDepartment of Gastroenterology and Hepatology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China.
Wen-Juan YangDepartment of Gastroenterology and Hepatology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China.
Bing HuDepartment of Gastroenterology and Hepatology, West China Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Crohn's disease (CD) is a chronic inflammatory bowel disease of unknown origin that can cause significant disability and morbidity with its progression. Due to the unique nature of CD, surgery is often necessary for many patients during their lifetime, and the incidence of postoperative complications is high, which can affect the prognosis of patients. Therefore, it is essential to identify and manage postoperative complications. Machine learning (ML) has become increasingly important in the medical field, and ML-based models can be used to predict postoperative complications of intestinal resection for CD. Recently, a valuable article titled "Predicting short-term major postoperative complications in intestinal resection for Crohn's disease: A machine learning-based study" was published by Wang

Indexed as

Crohn’s diseaseExplainabilityIntestinal resectionMachine learningPostoperative complications

Identifiers

PMID39220079
PMCPMC11362926

What OpenQuestion holds

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Registered trials

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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.