Literature DB >> 35283490

Some Methods for Substantiating Diagnostic Decisions Made Using Machine Learning Algorithms.

A G Losev1, I E Popov1, A Yu Petrenko1, A G Gudkov2, S G Vesnin3, S V Chizhikov2,4.   

Abstract

Various classification algorithms used in the diagnosis of breast cancer based on microwave radiometry data are considered. In particular, their principles of operation and the possibility of substantiating diagnoses using numerical data are discussed. A substantiation algorithm based on decision trees and a naive Bayesian classifier is presented. Examples of substantiation are given for breast cancer. © Springer Science+Business Media, LLC, part of Springer Nature 2022.

Entities:  

Year:  2022        PMID: 35283490      PMCID: PMC8898747          DOI: 10.1007/s10527-022-10153-y

Source DB:  PubMed          Journal:  Biomed Eng (NY)        ISSN: 0006-3398


  4 in total

1.  Justifying diagnosis decisions by deep neural networks.

Authors:  Graham Spinks; Marie-Francine Moens
Journal:  J Biomed Inform       Date:  2019-07-06       Impact factor: 6.317

Review 2.  Passive microwave radiometry in biomedical studies.

Authors:  Igor Goryanin; Sergey Karbainov; Oleg Shevelev; Alexander Tarakanov; Keith Redpath; Sergey Vesnin; Yuri Ivanov
Journal:  Drug Discov Today       Date:  2020-01-28       Impact factor: 7.851

3.  Passive Microwave Radiometry for the Diagnosis of Coronavirus Disease 2019 Lung Complications in Kyrgyzstan.

Authors:  Batyr Osmonov; Lev Ovchinnikov; Christopher Galazis; Berik Emilov; Mustafa Karaibragimov; Meder Seitov; Sergey Vesnin; Alexander Losev; Vladislav Levshinskii; Illarion Popov; Chingiz Mustafin; Turat Kasymbekov; Igor Goryanin
Journal:  Diagnostics (Basel)       Date:  2021-02-07

4.  Transparency as design publicity: explaining and justifying inscrutable algorithms.

Authors:  Michele Loi; Andrea Ferrario; Eleonora Viganò
Journal:  Ethics Inf Technol       Date:  2020-10-20
  4 in total

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