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A mill based instrument and software system for dissecting slide-mounted tissue that provides digital guidance and documentation

Overview of attention for article published in BMC Clinical Pathology, November 2013
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#4 of 115)
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

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1 X user
patent
7 patents

Citations

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10 Dimensions

Readers on

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19 Mendeley
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Title
A mill based instrument and software system for dissecting slide-mounted tissue that provides digital guidance and documentation
Published in
BMC Clinical Pathology, November 2013
DOI 10.1186/1472-6890-13-29
Pubmed ID
Authors

Nils Adey, Dale Emery, Derek Bosh, Steven Callahan, John Schreiner, Yang Chen, Ann Greig, Katherine Geiersbach, Robert Parry

Abstract

Dissection of specific Areas Of Interest (AOIs) of slide-mounted tumor samples is often used to enrich for cancer cells in order to generate better signal to noise ratios in subsequent biochemical characterization. Most clinical laboratories utilize manual dissection for practical reasons and to avoid the expense and difficulties of laser microdissection systems. Unfortunately, manual methods often lack resolution and process documentation. The goal of this project was to design a dissection system for slide-mounted tissue with better precision than manual methods that also provides digital image guidance and electronic process documentation.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 3 16%
Student > Bachelor 3 16%
Other 2 11%
Student > Ph. D. Student 2 11%
Student > Master 2 11%
Other 4 21%
Unknown 3 16%
Readers by discipline Count As %
Medicine and Dentistry 6 32%
Engineering 3 16%
Computer Science 2 11%
Agricultural and Biological Sciences 2 11%
Physics and Astronomy 1 5%
Other 1 5%
Unknown 4 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 September 2023.
All research outputs
#2,560,181
of 23,806,312 outputs
Outputs from BMC Clinical Pathology
#4
of 115 outputs
Outputs of similar age
#24,509
of 217,287 outputs
Outputs of similar age from BMC Clinical Pathology
#1
of 6 outputs
Altmetric has tracked 23,806,312 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 115 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done particularly well, scoring higher than 97% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 217,287 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them