Evidence map›Paper›PMID 36176930›Full record

ArticleContrast media & molecular imaging2022

Ligament Repair Method for Sports Dancers Based on Health Monitoring.

Jijin Sun, Yan Sheng

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Contrast media & molecular imaging, 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 It has been retracted, and should not be counted.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
0.5field-weighted citation impact, top 32% 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

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Jijin SunCollege of Education, Qiongtai Normal University, Haikou 571127, Hainan, China.
Yan ShengCollege of P. E, Qiongtai Normal University, Haikou 571127, Hainan, China.ORCID 0000-0002-0520-3531
Qiongtai Teachers College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In sports dance training, the injury rate of athletes' ligaments is higher than that of ordinary ones. Careful study of ligament repair methods can better prolong the sports life of sports dance athletes. The purpose of this paper is to investigate how to analyze ligament repair in sports dancers based on health monitoring. This paper proposes a deep learning algorithm based on health monitoring and a neural network algorithm, both of which have the function of prediction. The experimental results of this paper show that the common injuries in sports dance include ankle ligament injury, medial and lateral knee ligament strain, lumbar muscle strain, toe joint strain, shoulder deltoid strain and other injuries. Among them, the number of ankle ligament injuries is the largest, with 36 people, accounting for 30%. The number of people with medial and lateral ligament strains in the knee joint ranks second with 32 people, accounting for 26%. The total proportion of two kinds of ligament strains is 56%, accounting for more than half. It can be seen that ligament strains are the most common in sports dance injuries, so it is of great research significance to repair the ligaments of sports dancers based on health monitoring.

Indexed as

Ankle InjuriesDancingAnkle JointAthletesHumansLigaments

Identifiers

PMID36176930
PMCPMC9492416
OpenAlexW4295786894

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.