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Diagnostic Medical Classifiers
- 作者: Gavrikov B.M.1, Pestryakova N.V.1
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隶属关系:
- Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
- 期: 编号 3 (2024)
- 页面: 16-27
- 栏目: Intelligent systems and technologies
- URL: https://ogarev-online.ru/2071-8632/article/view/286111
- DOI: https://doi.org/10.14357/20718632240302
- EDN: https://elibrary.ru/BTQWIO
- ID: 286111
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详细
For the preliminary diagnosis of human diseases based on peripheral blood analysis, a statistical classification approach based on polynomial regression has been developed. It is implemented as two applications. One type of classifier allows you to assess the patient’s condition from healthy to the maximum degree of damage (oncology) within a separate body system. Using a different type of classifier, the area of tumor localization in cancer is identified. For various classification options, the structure of the training set is examined and a comparative analysis is carried out.
作者简介
Boris Gavrikov
Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
编辑信件的主要联系方式.
Email: bmgavrikov@gmail.com
аспирант
俄罗斯联邦, MoscowNadia Pestryakova
Federal Research Center “Computer Science and Control” of Russian Academy of Sciences
Email: pestryakova@isa.ru
Doctor of Technical Sciences, PhD in Physics and Mathematics
俄罗斯联邦, Moscow参考
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