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Article


Title

Exocytotic vesicle fusion classification for early disease diagnosis using a mobile GPU microsystem

Authors

[ 1 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ 2 ] Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] employee | [ SzD ] doctoral school student

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2022

Published in

Neural Computing and Applications

Journal year: 2022 | Journal volume: vol. 34 | Journal number: iss. 6

Article type

scientific article

Publication language

english

Keywords
EN
  • GPU
  • perceptron
  • amperometry
  • exocytosis
  • vesicle fusion
  • precancerous condition
Abstract

EN This work addresses monitoring vesicle fusions occurring during the exocytosis process, which is the main way of intercellular communication. Certain vesicle behaviors may also indicate certain precancerous conditions in cells. For this purpose we designed a system able to detect two main types of exocytosis: a full fusion and a kiss-and-run fusion, based on data from multiple amperometric sensors at once. It uses many instances of small perceptron neural networks in a massively parallel manner and runs on Jetson TX2 platform, which uses a GPU for parallel processing. Based on performed benchmarking, approximately 140,000 sensors can be processed in real time within the sensor sampling period equal to 10 ms and an accuracy of 99%. The work includes an analysis of the system performance with varying neural network sizes, input data sizes, and sampling periods of fusion signals.

Date of online publication

12.11.2021

Pages (from - to)

4843 - 4854

DOI

10.1007/s00521-021-06676-2

URL

https://link.springer.com/article/10.1007/s00521-021-06676-2

License type

CC BY (attribution alone)

Open Access Mode

czasopismo hybrydowe

Open Access Text Version

final published version

Date of Open Access to the publication

in press

Points of MNiSW / journal

100.0

Impact Factor

5.606 [List 2020]

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