Evidence map›Paper›PMID 28044087›Full record

ArticleComputational and mathematical methods in medicine2016

Statistical Analyses of Femur Parameters for Designing Anatomical Plates.

Lin Wang, Kunjin He, Zhengming Chen

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

3 authors.

Lin WangCollege of Internet of Things Engineering, Hohai University, Changzhou, China; Changzhou City Key Lab of Orthopaedic Implants Digital Technology, Changzhou, China.ORCID 0000-0001-6894-6474
Kunjin HeCollege of Internet of Things Engineering, Hohai University, Changzhou, China; Changzhou City Key Lab of Orthopaedic Implants Digital Technology, Changzhou, China.ORCID 0000-0001-9436-6457
Zhengming ChenCollege of Internet of Things Engineering, Hohai University, Changzhou, China; Changzhou City Key Lab of Orthopaedic Implants Digital Technology, Changzhou, China.ORCID 0000-0002-5763-1503

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Femur parameters are key prerequisites for scientifically designing anatomical plates. Meanwhile, individual differences in femurs present a challenge to design well-fitting anatomical plates. Therefore, to design anatomical plates more scientifically, analyses of femur parameters with statistical methods were performed in this study. The specific steps were as follows. First, taking eight anatomical femur parameters as variables, 100 femur samples were classified into three classes with factor analysis and Q-type cluster analysis. Second, based on the mean parameter values of the three classes of femurs, three sizes of average anatomical plates corresponding to the three classes of femurs were designed. Finally, based on Bayes discriminant analysis, a new femur could be assigned to the proper class. Thereafter, the average anatomical plate suitable for that new femur was selected from the three available sizes of plates. Experimental results showed that the classification of femurs was quite reasonable based on the anatomical aspects of the femurs. For instance, three sizes of condylar buttress plates were designed. Meanwhile, 20 new femurs are judged to which classes the femurs belong. Thereafter, suitable condylar buttress plates were determined and selected.

Indexed as

AlgorithmsBayes TheoremBone PlatesCluster AnalysisDiscriminant AnalysisFemurHealthy VolunteersHumansImage Processing, Computer-AssistedImaging, Three-DimensionalModels, AnatomicModels, StatisticalProsthesis DesignSoftwareStress, Mechanical

Identifiers

PMID28044087
PMCPMC5156872

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.