Evidence map›Paper›PMID 28239236›Full record

ArticleMeasurement science & technology2017

Assessing composition and structure of soft biphasic media from Kelvin-Voigt fractional derivative model parameters.

Hong Mei Zhang, Yue Wang, Mostafa Fatemi, Michael F Insana

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Measurement science & technology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 30% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 2 institutions in 2 countries.

Hong Mei ZhangKey Laboratory of Biomedical Information Engineering, Ministry of Education, School of Life Science and Technology, Xi'an JiaoTong University, Xianning West Road No.28, Xi'an, Shaanxi, 710049, P. R. China; Department of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana IL, 61801, USA.
Yue WangDepartment of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana IL, 61801, USA.
Mostafa FatemiDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, MN, USA.
Michael F InsanaDepartment of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana IL, 61801, USA.
University of Illinois Urbana-Champaign · USMayo Clinic · US

Funding

Classification of breast masses based on visco-elastic propertiesR01CA168575 · NCI · MAYO CLINIC ROCHESTER · PI FATEMI, MOSTAFA, INSANA, MICHAEL F · 2013 to 2018
$2.5M
NCI NIH HHS R01 CA168575
6 · The paper itself

Abstract

Kelvin-Voigt fractional derivative (KVFD) model parameters have been used to describe viscoelastic properties of soft tissues. However, translating model parameters into a concise set of intrinsic mechanical properties related to tissue composition and structure remains challenging. This paper begins by exploring these relationships using a biphasic emulsion materials with known composition. Mechanical properties are measured by analyzing data from two indentation techniques - ramp-stress relaxation and load-unload hysteresis tests. Material composition is predictably correlated with viscoelastic model parameters. Model parameters estimated from the tests reveal that elastic modulus

Indexed as

Ex vivo livergelatin emulsionsindentationKVFDviscoelastic modeling

Identifiers

PMID28239236
PMCPMC5319561
OpenAlexW2565967484

What OpenQuestion holds

Textmetadata
LicenceTDM
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.