Abstract
“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%.
Highlights
Most of the methods of early diagnosis of malignant neoplasms are invasive, operator-dependent and expensive
In this work the diagnosis of oncological diseases is a classification task, and that is why the perceptron was chosen as the architecture of the neural network
16 × 14 values obtained from gas sensors, such as age, sex and smoking, were fed to the input of the neural network
Summary
Most of the methods of early diagnosis of malignant neoplasms are invasive, operator-dependent and expensive. Treatment of patients with locally advanced malignant tumors of the oropharyngeal region and larynx is often associated with a whole complex of negative consequences: disability, impaired physiological functions, severe cosmetic losses and the occurrence of psycho-emotional trauma [3] This circumstance directs clinical oncologists and specialists in related fields to search for affordable and effective methods for diagnosing malignant tumors at early stages, which reflects modern principles of screening methods for diagnosing tumors of the oropharyngeal region and larynx - reproducibility, low cost, independence from the human factor (reduction of error), and the possibility of use in non-specialized clinics by primary care physicians (therapists, ENT doctors, dentists) [4]
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