Evidence map›Paper›PMID 36612790›Full record

ArticleInternational journal of environmental research and public health2022

A Systematic Analysis of 3D Deformation of Aging Breasts Based on Artificial Neural Networks.

Jun Zhang, Ruixin Liang, Newman Lau, Qiwen Lei, Joanne Yip

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Jun ZhangSchool of Fashion and Textiles, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China.
Ruixin LiangLaboratory for Artificial Intelligence in Design, Hong Kong Science Park, New Territories, Hong Kong, China.
Newman LauSchool of Design, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China.ORCID 0000-0001-8668-9467
Qiwen LeiSchool of Fashion and Textiles, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China.
Joanne YipSchool of Fashion and Textiles, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China.ORCID 0000-0002-3270-4702

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The measurement and prediction of breast skin deformation are key research directions in health-related research areas, such as cosmetic and reconstructive surgery and sports biomechanics. However, few studies have provided a systematic analysis on the deformations of aging breasts. Thus, this study has developed a model order reduction approach to predict the real-time strain of the breast skin of seniors during movement. Twenty-two women who are on average 62 years old participated in motion capture experiments, in which eight body variables were first extracted by using the gray relational method. Then, backpropagation artificial neural networks were built to predict the strain of the breast skin. After optimization, the R-value for the neural network model reached 0.99, which is within acceptable accuracy. The computer-aided system of this study is validated as a robust simulation approach for conducting biomechanical analyses and predicting breast deformation.

Indexed as

BreastNeural Networks, ComputerBiomechanical PhenomenaComputer SimulationFemaleHumansMiddle AgedMovementbackpropagation artificial neural networkbreast skin deformationcomputer-aided systemgray relational analysis

Identifiers

PMID36612790
PMCPMC9819929

What OpenQuestion holds

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Registered trials

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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.