Evidence map›Paper›PMID 35368947›Full record

ArticleJournal of healthcare engineering2022

Role of CT Images in the Diagnosis of Common Acute Abdominal Diseases in General Surgery.

Yunguang Nan, Zuyan Zhang, Jianbo Zhang, Bo Jiang, Yuxi Zhu, Li Zhang

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Journal of healthcare engineering, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Yunguang NanGeneral Surgery, Shuyang Benevolent Hospital, Suqian 223600, Jiangsu, China.
Zuyan ZhangImaging Department, Shuyang Benevolent Hospital, Suqian 223600, Jiangsu, China.
Jianbo ZhangGeneral Surgery, Shuyang Benevolent Hospital, Suqian 223600, Jiangsu, China.
Bo JiangGeneral Surgery, Shuyang Benevolent Hospital, Suqian 223600, Jiangsu, China.
Yuxi ZhuGeneral Surgery, Shuyang Benevolent Hospital, Suqian 223600, Jiangsu, China.ORCID 0000-0002-8659-844X
Li ZhangImaging Department, Shuyang Benevolent Hospital, Suqian 223600, Jiangsu, China.ORCID 0000-0002-5425-0721

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute abdomen is a clinical emergency disease with acute abdominal pain as the main prominent feature. Through severe disease changes in intra-abdominal, extrapelvic, and retroperitoneal tissues and organs, symptoms and clinical signs led by abdominal pain are formed. This article mainly explores the role of CT imaging diagnosis in common acute abdominal diseases in general surgery. In this paper, the use of computer-aided CT scan imaging technology in pulmonary nodules was firstly investigated, and the image segmentation algorithms based on CT images were given, including the spatial domain fuzzy C-mean clustering separation algorithm and the spatial domain fuzzy clustering level set semiautomatic separation algorithm, then the treatment of acute abdomen under the concept of ERAS was explored, and the treatment of ERAS under CT images of the acute abdomen was analyzed and studied. The empirical research results show that the ERAS's concept is guided by the undergoing national nutritional support with the traditional perioperative management. Compared to 12.9% of complications in traditional CPM groups, the recall rate of complications after ERAS group was only 6.01%, the improvement was obvious and the results were statistically significant (

Indexed as

AlgorithmsTomography, X-Ray ComputedCluster AnalysisHumans

Identifiers

PMID35368947
PMCPMC8967512
OpenAlexW4221055722

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.