Please use this identifier to cite or link to this item:
http://repositsc.nuczu.edu.ua/handle/123456789/12349
Title: | Machine Learning Methods in Medicine Diagnostics Problems |
Authors: | Угрюмов, Михайло Гончарова, Тамара Стрілець, Вікторія |
Keywords: | medicine diagnostics, machine learning, artificial neural network, ROC-curve, confusion matrix. |
Issue Date: | 6-Oct-2020 |
Citation: | (ICTERI 2020) Integration ,Harmonization and Knowledge Transfer. Volume II: Workshops. Kharkiv, Ukraine, |
Abstract: | Medical service improvement has always been a life topical problem. To decide it, we must continuously raise the competency of doctors and develop new methods and approaches which could help take decisions concerning diagnostics (classification of patient health conditions such as: Naive Bayes Classifier, Linear Classifier, Support-vector machine, K-nearest Neighbor Classifier, Logistic Regression, Decision Tree Classifier, Random Forest Classifier, Ada Boost Classifier and Artificial Neural Network. A radial basis network was chosen from the variety of artificial neural system architectures to solve classification tasks. |
URI: | http://repositsc.nuczu.edu.ua/handle/123456789/12349 |
Appears in Collections: | Кафедра управління та організації діяльності у сфері цивільного захисту |
Files in This Item:
File | Description | Size | Format | |
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Methods of machine learning in medicine diagnostics tasks.doc | 1,56 MB | Microsoft Word | View/Open |
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