Cancer Diagnosis by Neural Network Analysis of Data from Semiconductor Sensors / V. I. Chernov, E. L. Choynzonov, D. E. Kulbakin [et al.]

Уровень набора: DiagnosticsАльтернативный автор-лицо: Chernov, V. I., specialist in the field of medical technology, lead engineer of Tomsk Polytechnic University, doctor of medical sciences, 1962-, Vladimir Ivanovich;Choynzonov, E. L., physicist, chief expert of Tomsk Polytechnic University, 1952-, Evgeny Lkhamatsyrenovich;Kulbakin, D. E., Denis Evgenjevich;Obkhodskaya, E. V., Elena Vladimirovna;Obkhodskiy, A. V., specialist in the field of nuclear power engineering, Associate Professor of Tomsk Polytechnic University, Candidate of technical science, 1982-, Artem Viktorovich;Popov, A. S., physicist, Design Engineer of Tomsk Polytechnic University, 1992-, Aleksandr Sergeevich;Sachkov, V. I., chemist, Associate Professor of Tomsk Polytechnic University, Candidate of chemical sciences, 1978-, Viktor Ivanovich;Sachkova, A. S., biologist, Associate Professor of Tomsk Polytechnic University, candidate of biological sciences, 1986-, Anna SergeevnaКоллективный автор (вторичный): Национальный исследовательский Томский политехнический университет, Инженерная школа ядерных технологий, Отделение ядерно-топливного циклаЯзык: английский.Резюме или реферат: “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%..Примечания о наличии в документе библиографии/указателя: [References: 43 tit.].Тематика: электронный ресурс | труды учёных ТПУ | malignant neoplasm | classification | electronic nose | neural network | metal oxide semiconductor sensor | gas analyzer | злокачественные новообразования | нейронные сети | газоанализаторы Ресурсы он-лайн:Щелкните здесь для доступа в онлайн
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[References: 43 tit.]

“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%.

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