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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 respiratory...

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Detalles Bibliográficos
Autores principales: Chernov, Vladimir I., Choynzonov, Evgeniy L., Kulbakin, Denis E., Obkhodskaya, Elena V., Obkhodskiy, Artem V., Popov, Aleksandr S., Sachkov, Victor I., Sachkova, Anna S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7555125/
https://www.ncbi.nlm.nih.gov/pubmed/32899544
http://dx.doi.org/10.3390/diagnostics10090677
Descripción
Sumario:“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%.