Evidence map›Paper›PMID 35720919›Full record

ArticleComputational intelligence and neuroscience2022

Design of Growth Trend Map of Children and Adolescents Based on Bone Age.

Kaiyan Chen, Weiyuan Shi, Keji Mao, Wenxiu He, Ahmedin M Ahmed, Kai Fang

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. 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
–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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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  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

6 authors.

Kaiyan ChenCollege of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China.ORCID https://orcid.org/0000-0002-1411-7635
Weiyuan ShiCollege of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China.
Keji MaoCollege of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China.ORCID https://orcid.org/0000-0002-5021-378X
Wenxiu HeCollege of Zhijiang, Zhejiang University of Technology, Shaoxing, China.
Ahmedin M AhmedFlorida International University, Miami, FL, USA.
Kai FangCollege of Electrical and Information Engineering, Quzhou University, Quzhou, Zhejiang 324000, China.ORCID https://orcid.org/0000-0003-0419-1468

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate height prediction has important reference significance for the development of children and adolescents and the selection of athletes. The current mainstream height prediction methods include the B-P (Bayley-Pinneau) method and the TW2 (Tanner-Whitehouse) method. A large number of documents show that the B-P method and the TW2 method have relatively large deviations in the lifelong height prediction results of Chinese children and adolescents. Based on the data collected by the Chinese Adolescent Students' Physical Fitness and Growth and Development Health Project in Zhejiang's primary and secondary schools, this paper proposes a graph of height growth trends based on bone age. The height map of age has more reference value. Aiming at the feasibility of the height data in the statistical results, the interpolation prediction method is used to verify the data, and the height growth trend graph is drawn through the method of fitting. Validation results with actual data show that the average error of the lifetime height prediction of the height growth trend map proposed in this paper is 2.1 cm, which is 1.4 cm lower than the 3.5 cm error predicted by the B-P method and 0.4 cm lower than the 2.5 cm error predicted by the TW2 method.

Indexed as

Body HeightResearch DesignAdolescentChildHumans

Identifiers

PMID35720919
PMCPMC9205695

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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.