Using convolutional neural networks for breast cancer diagnosing

dc.contributor.authorNaderan, M.
dc.contributor.authorZaychenko, Yu.
dc.contributor.authorNapoli, A.
dc.date.accessioned2022-05-18T09:18:16Z
dc.date.available2022-05-18T09:18:16Z
dc.date.issued2019
dc.description.abstractenDuring the last few years, Convolutional Neural Networks (CNN) have been widely used in Computer-Aided Detection and the medical image analysis. The main idea of this paper is to modify CNN’s architectures to achieve the better sensitivity and the precision for detecting breast cancer at an early stage compared to existing methods. For this purpose, several factors were considered before CNN training such as the data processing, model, dataset, etc. In the proposed model the following hyperparameters were the following: the dropout rate 0,2, epoch 38 and batch size 33. Besides the hyperparameters, two fully connected layers in the modified model were used. An average recall (sensitivity) in the recent works was 74%. The precision and recall of proposed model for breast cancer classification were 66,66% and 85,7%, respectively.uk
dc.format.pagerangeС. 85-93uk
dc.identifier.citationNaderan, M. Using convolutional neural networks for breast cancer diagnosing / M. Naderan, Yu. Zaychenko, A. Napoli // Системні дослідження та інформаційні технології : міжнародний науково-технічний журнал. – 2019. – № 4. – С. 85-93. – Бібліогр.: 20 назв.uk
dc.identifier.doihttps://doi.org/10.20535/SRIT.2308-8893.2019.4.09
dc.identifier.urihttps://ela.kpi.ua/handle/123456789/47401
dc.language.isoenuk
dc.publisherКПІ ім. Ігоря Сікорськогоuk
dc.publisher.placeКиївuk
dc.sourceСистемні дослідження та інформаційні технології, № 4uk
dc.subjectconvolutional neural networksuk
dc.subjectdeep learninguk
dc.subjectcomputer-aided detectionuk
dc.subjectbreast cancer diagnosisuk
dc.subjectclassificationuk
dc.subject.udc004.855.5uk
dc.titleUsing convolutional neural networks for breast cancer diagnosinguk
dc.typeArticleuk

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