Evidence map›Paper›PMID 34712300›Full record

ArticlePakistan journal of medical sciences2021

Brain tissue development of neonates with Congenital Septal Defect: Study on MRI Image Evaluation of Deep Learning Algorithm.

Jianfei Zhu, Jiaolei Chen, Yunhui Zhang, Jianwei Ji

Open access · goldAbstract read
In one paragraph

Article in Pakistan journal of medical sciences, 2021. 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
0.3field-weighted citation impact, top 40% 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, 2 citations in OpenAlex.

  1. 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

4 authors at 1 institution in 1 country.

Jianfei ZhuJianfei Zhu, Attending Physician. Department of Neonatology, Yiwu Central Hospital, Yiwu, 322000, China.
Jiaolei ChenJiaolei Chen, Attending Physician. Department of Neonatology, Yiwu Central Hospital, Yiwu, 322000, China.
Yunhui ZhangYunhui Zhang, Attending Physician. Department of Neonatology, Yiwu Central Hospital, Yiwu, 322000, China.
Jianwei JiJianwei Ji, Attending Physician. Department of Neonatology, Yiwu Central Hospital, Yiwu, 322000, China.
Yichang Central People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis article is based on deep learning algorithms and uses MRI to study the development of congenital heart septal defects in neonatal brain tissue.

methodsFrom January 2018 to December 2019, 150 cases of congenital cardiac paper septal defect were retrospectively analyzed on 50 cases of normal newborns and neonates. The four index parametersbrain MR imaging, lateral ventricle pre-angle measurement index (F/F'), body index (D/ D'), caudal nucleus index (C/C') were analyzed. The independent sample t test is performed to compare the difference parameters between groups.

resultsF congenital heart disease group and control group/F 'values were 0.301 ± 0.035 and 0.296 ± 0.031; Evans index was 0.239 ± 0.052 and 0.233 ± 0.025; 2 sets of D/D' values were 0.261 ± 0.039 and 0.234 ± 0.032; C/C 'value was 0.138 ± 0.018 and 0.124 ± 0.015 respectively. The congenital heart disease group D/D ', and the value of C/C' obtained under the ROC curve area value, respectively 0.698 and 0.750, Youden index corresponding to the maximum D/D ', and the value of C/C' values were 0.28 and 0.12.

conclusionLateral ventricle D/D 'and C/C' is more sensitive indicator which can be evaluated with the difference between the volume of congenital heart septal defects in newborn normal neonatal brain; when the D/D 'value> 0.28, C/C' value> 0.12. For the diagnosis and evaluation of congenital heart septal defect neonatal brain volume abnormalities have a certain reference value.

Indexed as

Brain TissueCongenital Septal DefectDeep Learning AlgorithmMRI Image EvaluationNeonates

Identifiers

PMID34712300
PMCPMC8520356
OpenAlexW3191891445

What Socratic 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 Socratic graph.