Поиск по репозиторию
Статья
Cancer Diagnosis by Neural Network Analysis of Data from Semiconductor Sensors
2021
“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%. © 2020 by the authors. Licensee MDPI, Basel, Switzerland
Цитирование
Похожие публикации
Версии
- 1. Version of Record от 2021-04-27
Метаданные
Название журнала
- Diagnostics
Том
- 10
Выпуск
- 9
Страницы
- -
Ключевые слова
- membrane protein; metal oxide; silica gel; zeolite; adult; aged; Article; artificial neural network; breath analysis; cancer diagnosis; cancer screening; coronavirus disease 2019; data analysis; diagnostic accuracy; diagnostic test accuracy study; expired air; female; gas analysis; human; k nearest neighbor; larynx cancer; lung cancer; major clinical study; male; malignant neoplasm; mouth cancer; oropharynx cancer; perceptron; respiratory tract cancer; sensitivity and specificity; support vector machine; tongue cancer
Издатель
- MDPI AG
Тип документа
- journal article
Тип лицензии Creative Commons
- CC
Правовой статус документа
- Свободная лицензия
Источник
- scopus
