Zanotti, Michele (2022) A neural network analysis of a dataset obtained through a carbon nanotube sensor array for breathomics applications. Il nuovo cimento C, 45 (4). pp. 1-7. ISSN 1826-9885
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Official URL: https://www.sif.it/riviste/sif/ncc/econtents/2022/...
Abstract
In this study, a dataset collected with a carbon nanotube based sensor array is analyzed to discriminate healthy from sick patients affected by chronic obstructive pulmonary disease (COPD). The dataset is analyzed with two approaches, the Principal Component Analysis (PCA) and the Neural Network. A comparison between the results obtained with these two methods is made. The applicability of the Neural Network is discussed, along with methods used to avoid the over-fitting problem.
Item Type: | Article |
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Subjects: | 500 Scienze naturali e Matematica > 530 Fisica |
Depositing User: | Marina Spanti |
Date Deposited: | 06 Sep 2022 11:39 |
Last Modified: | 06 Sep 2022 11:39 |
URI: | http://eprints.bice.rm.cnr.it/id/eprint/21997 |
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