Application of Artifical Neural Networks for Processing Some Biomedical Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F24%3A43972308" target="_blank" >RIV/49777513:23220/24:43972308 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10577768" target="_blank" >https://ieeexplore.ieee.org/document/10577768</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/MECO62516.2024.10577768" target="_blank" >10.1109/MECO62516.2024.10577768</a>
Alternative languages
Result language
angličtina
Original language name
Application of Artifical Neural Networks for Processing Some Biomedical Data
Original language description
Artificial neural networks (ANN) are used for modeling, adaptive control, curve fitting and other applications where they can be trained by a measured data. ANNs are used as an auxiliary tool of artificial intelligence. ANN can learn from training results and can evaluate conclusions from a complex and evidently unrelated set of information. Increasingly, ANNs are used in wide range of applications and also in biomedical engineering. In this contribution, simple applications from the field of medical engineering, especially in exercise testing data evaluation are presented. It should be noted that all data was obtained by real measurement. All examples were processed using Matlab's Neural Toolbox.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20601 - Medical engineering
Result continuities
Project
<a href="/en/project/EF18_069%2F0009855" target="_blank" >EF18_069/0009855: Electrical Engineering Technologies with High-Level of Embedded Intelligence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<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
Article name in the collection
2024 13th Mediterranean Conference on Embedded Computing (MECO)
ISBN
979-8-3503-8756-8
ISSN
2377-5475
e-ISSN
2637-9511
Number of pages
4
Pages from-to
412-415
Publisher name
IEEE
Place of publication
Piscataway
Event location
Budva, Montenegro
Event date
Jun 11, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001268606200001