Application of artificial intelligence in microwave radiometry (MWR)

Christoforos Galazis, Sergey Vesnin, Igor Goryanin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Microwave radiometry is being developed more actively in recent years for medical applications. One such application is for diagnosis or monitoring of cancer. Medical radiometry presents a strong alternative to other methods of diagnosis, especially with recent gains in its accuracy. In addition, it is safe to use, noninvasive and has a relative low cost of use. Temperature readings were taking from the mammary glands for the purpose of detecting cancer and evaluating the effectiveness of radiometry. Building a diagnostic system to automate classification of new samples requires an adequate machine learning model. Such models that were explored were random forest, XGBoost, k-nearest neighbors, support vector machines, variants of cascade correlation neural network, deep neural network and convolution neural network. From all these models evaluated, the best performing on the test set was the deep neural network with a significant difference from the rest.

Original languageEnglish
Title of host publicationProceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: BIOINFORMATICS
EditorsElisabetta De Maria, Hugo Gamboa, Ana Fred
PublisherSCITEPRESS
Pages112-122
Number of pages11
Volume4
ISBN (Electronic)978-989-758-353-7
DOIs
Publication statusPublished - 24 Feb 2019
Event10th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2019 - Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019 - Prague, Czech Republic
Duration: 22 Feb 201924 Feb 2019

Publication series

Name
PublisherSCITEPRESS
ISSN (Electronic)2184-4305

Conference

Conference10th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2019 - Part of 12th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2019
CountryCzech Republic
CityPrague
Period22/02/1924/02/19

Keywords

  • Artificial Intelligence
  • Breast Cancer
  • Cascade Correlation Neural Network
  • Convolutional Neural Network
  • Diagnostic System
  • Machine Learning
  • Microwave Radiometry
  • Neural Network
  • Random Forest
  • Support Vector Machine

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