Cancer Diagnosis by Neural Network Analysis of Data from Semiconductor Sensors

"Electronic nose" technology, including technical and software tools to analyze gas mixtures, is promising regarding the diagnosis of malignant neoplasms. This paper presents the research results of breath samples analysis from 59 people, including patients with a confirmed diagnosis of re...

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Bibliographic Details
Published in:Diagnostics (Basel) 2020-09, Vol.10 (9), p.677
Main Authors: Chernov, Vladimir I, Choynzonov, Evgeniy L, Kulbakin, Denis E, Obkhodskaya, Elena V, Obkhodskiy, Artem V, Popov, Aleksandr S, Sachkov, Victor I, Sachkova, Anna S
Format: Article
Language:English
Subjects:
Accuracy
Breast cancer
Chromatography
classification
electronic nose
gas analyzer
Gases
Larynx
Lung cancer
malignant neoplasm
metal oxide semiconductor sensor
Methods
neural network
Neural networks
Prostate
Sensors
Tumors
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Description
Summary:"Electronic nose" technology, including technical and software tools to analyze gas mixtures, is promising regarding the diagnosis of malignant neoplasms. This paper presents the research results of breath samples analysis from 59 people, including patients with a confirmed diagnosis of respiratory tract cancer. The research was carried out using a gas analytical system including a sampling device with 14 metal oxide sensors and a computer for data analysis. After digitization and preprocessing, the data were analyzed by a neural network with perceptron architecture. As a result, the accuracy of determining oncological disease was 81.85%, the sensitivity was 90.73%, and the specificity was 61.39%.
ISSN:2075-4418
2075-4418
DOI:10.3390/diagnostics10090677