Evidence map›Paper›PMID 28203270›Full record

ArticleComputational and mathematical methods in medicine2017

A Novel Computer-Aided Approach for Parametric Investigation of Custom Design of Fracture Fixation Plates.

Xiaozhong Chen, Kunjin He, Zhengming Chen

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.9field-weighted citation impact, top 9% 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

4 citing papers in PubMed, 30 citations in OpenAlex.

  1. Article
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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 at 1 institution in 1 country.

Xiaozhong ChenCollege of Internet of Things Engineering, Hohai University, Changzhou, China; School of Intelligent Equipment and Information Engineering, Changzhou Vocational Institute of Engineering, Jiangsu, China.ORCID 0000-0003-4351-9753
Kunjin HeCollege of Internet of Things Engineering, Hohai University, Changzhou, China; Changzhou City Key Lab of Orthopedic Implants Digital Technology, Changzhou, China.ORCID 0000-0002-0843-858X
Zhengming ChenCollege of Internet of Things Engineering, Hohai University, Changzhou, China; Changzhou City Key Lab of Orthopedic Implants Digital Technology, Changzhou, China.ORCID 0000-0002-5763-1503
Hohai University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study proposes an integrated computer-aided approach combining femur surface modeling, fracture evidence recover plate creation, and plate modification in order to conduct a parametric investigation of the design of custom plate for a specific patient. The study allows for improving the design efficiency of specific plates on the patients' femur parameters and the fracture information. Furthermore, the present approach will lead to exploration of plate modification and optimization. The three-dimensional (3D) surface model of a detailed femur and the corresponding fixation plate were represented with high-level feature parameters, and the shape of the specific plate was recursively modified in order to obtain the optimal plate for a specific patient. The proposed approach was tested and verified on a case study, and it could be helpful for orthopedic surgeons to design and modify the plate in order to fit the specific femur anatomy and the fracture information.

Indexed as

Bone PlatesComputer-Aided DesignFracture Fixation, InternalProsthesis DesignAlgorithmsComputer SimulationFemaleFemoral FracturesFemurHumansImaging, Three-DimensionalMedical InformaticsOrthopedics

Identifiers

PMID28203270
PMCPMC5288515
OpenAlexW2580737643

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.