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3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors

Overview of attention for article published in Advanced Materials Technologies, December 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#10 of 1,094)
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

news
27 news outlets
blogs
5 blogs
twitter
10 X users
video
1 YouTube creator

Citations

dimensions_citation
63 Dimensions

Readers on

mendeley
167 Mendeley
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Title
3D Printed Organ Models with Physical Properties of Tissue and Integrated Sensors
Published in
Advanced Materials Technologies, December 2017
DOI 10.1002/admt.201700235
Pubmed ID
Authors

Kaiyan Qiu, Zichen Zhao, Ghazaleh Haghiashtiani, Shuang‐Zhuang Guo, Mingyu He, Ruitao Su, Zhijie Zhu, Didarul B. Bhuiyan, Paari Murugan, Fanben Meng, Sung Hyun Park, Chih‐Chang Chu, Brenda M. Ogle, Daniel A. Saltzman, Badrinath R. Konety, Robert M. Sweet, Michael C. McAlpine

Abstract

The design and development of novel methodologies and customized materials to fabricate patient-specific 3D printed organ models with integrated sensing capabilities could yield advances in smart surgical aids for preoperative planning and rehearsal. Here, we demonstrate 3D printed prostate models with physical properties of tissue and integrated soft electronic sensors using custom-formulated polymeric inks. The models show high quantitative fidelity in static and dynamic mechanical properties, optical characteristics, and anatomical geometries to patient tissues and organs. The models offer tissue-mimicking tactile sensation and behavior and thus can be used for the prediction of organ physical behavior under deformation. The prediction results show good agreement with values obtained from simulations. The models also allow the application of surgical and diagnostic tools to their surface and inner channels. Finally, via the conformal integration of 3D printed soft electronic sensors, pressure applied to the models with surgical tools can be quantitatively measured.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 X users 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 167 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 167 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 33 20%
Student > Master 22 13%
Researcher 20 12%
Student > Bachelor 16 10%
Student > Doctoral Student 12 7%
Other 22 13%
Unknown 42 25%
Readers by discipline Count As %
Engineering 54 32%
Materials Science 18 11%
Medicine and Dentistry 12 7%
Agricultural and Biological Sciences 6 4%
Chemistry 6 4%
Other 21 13%
Unknown 50 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 217. 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 31 January 2023.
All research outputs
#177,692
of 25,376,589 outputs
Outputs from Advanced Materials Technologies
#10
of 1,094 outputs
Outputs of similar age
#3,677
of 444,642 outputs
Outputs of similar age from Advanced Materials Technologies
#2
of 20 outputs
Altmetric has tracked 25,376,589 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,094 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.6. This one has done particularly well, scoring higher than 99% 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 444,642 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.