Automating data classification for label-free point-of-care biosensing in real complex samples
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378271%3A_____%2F24%3A00599585" target="_blank" >RIV/68378271:_____/24:00599585 - isvavai.cz</a>
Result on the web
<a href="https://hdl.handle.net/11104/0357035" target="_blank" >https://hdl.handle.net/11104/0357035</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.sna.2024.115501" target="_blank" >10.1016/j.sna.2024.115501</a>
Alternative languages
Result language
angličtina
Original language name
Automating data classification for label-free point-of-care biosensing in real complex samples
Original language description
Surface-based affinity biosensors present a promising avenue for point-of-care (POC) pathogen detection in real-world samples. This paper introduces a procedure for automatically classifying pathogen presence in unprocessed liquids from direct detection data measured by a simple POC quartz crystal microbalance sensor device. We show that the developed procedure exhibits exceptional robustness across different biosensing assays and complex real-world media. Through optimizing parameters using diverse datasets encompassing Escherichia coli O157:H7 (E. coli) and SARS-CoV-2 detection in various media, we achieved rates of successful detection as high as 80.8 % and 90.9 % for E. coli and SARS-CoV-2, respectively, without extensive machine learning. Our results suggest that this exceptionally robust method holds potential as a straightforward tool for automating sample classification in point-of-care diagnostics, underpinning its promising broader applicability.
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
10610 - Biophysics
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Sensors and Actuators A - Physical
ISSN
0924-4247
e-ISSN
1873-3069
Volume of the periodical
374
Issue of the periodical within the volume
Aug
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
8
Pages from-to
115501
UT code for WoS article
001246546400001
EID of the result in the Scopus database
2-s2.0-85194105928