IsletSwipe, a mobile platform for expert opinion exchange on islet graft images
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388963%3A_____%2F23%3A00571406" target="_blank" >RIV/61388963:_____/23:00571406 - isvavai.cz</a>
Alternative codes found
RIV/67985823:_____/23:00571406 RIV/00023001:_____/23:00083823
Result on the web
<a href="https://doi.org/10.1080/19382014.2023.2189873" target="_blank" >https://doi.org/10.1080/19382014.2023.2189873</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/19382014.2023.2189873" target="_blank" >10.1080/19382014.2023.2189873</a>
Alternative languages
Result language
angličtina
Original language name
IsletSwipe, a mobile platform for expert opinion exchange on islet graft images
Original language description
We previously developed a deep learning-based web service (IsletNet) for an automated counting of isolated pancreatic islets. The neural network training is limited by the absent consensus on the ground truth annotations. Here, we present a platform (IsletSwipe) for an exchange of graphical opinions among experts to facilitate the consensus formation. The platform consists of a web interface and a mobile application. In a small pilot study, we demonstrate the functionalities and the use case scenarios of the platform. Nine experts from three centers validated the drawing tools, tested precision and consistency of the expert contour drawing, and evaluated user experience. Eight experts from two centers proceeded to evaluate additional images to demonstrate the following two use case scenarios. The Validation scenario involves an automated selection of images and islets for the expert scrutiny. It is scalable (more experts, images, and islets may readily be added) and can be applied to independent validation of islet contours from various sources. The Inquiry scenario serves the ground truth generating expert in seeking assistance from peers to achieve consensus on challenging cases during the preparation for IsletNet training. This scenario is limited to a small number of manually selected images and islets. The experts gained an opportunity to influence IsletNet training and to compare other experts’ opinions with their own. The ground truth-generating expert obtained feedback for future IsletNet training. IsletSwipe is a suitable tool for the consensus finding. Experts from additional centers are welcome to participate.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Islets
ISSN
1938-2014
e-ISSN
1938-2022
Volume of the periodical
15
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
15
Pages from-to
2189873
UT code for WoS article
000959035100001
EID of the result in the Scopus database
2-s2.0-85151112347