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Extreme Learning Machine (ELM)-Based Classification of Benign and Malignant Cells in Breast Cancer

BACKGROUND: Breast cancer is one of the most common cancer types in the world and is a serious threat to health. This type of cancer is complex; it is a hereditary disease and does not result from a single cause. The diagnosis of cancer starts with a biopsy. Various methods are used to detect and re...

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Autor principal: Toprak, Abdullah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6154116/
https://www.ncbi.nlm.nih.gov/pubmed/30222727
http://dx.doi.org/10.12659/MSM.910520
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author Toprak, Abdullah
author_facet Toprak, Abdullah
author_sort Toprak, Abdullah
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description BACKGROUND: Breast cancer is one of the most common cancer types in the world and is a serious threat to health. This type of cancer is complex; it is a hereditary disease and does not result from a single cause. The diagnosis of cancer starts with a biopsy. Various methods are used to detect and recognize cancer cells, from microscopic images and mammography to ultrasonography and magnetic resonance images (MRI). MATERIAL/METHODS: Detection and characterization of benign and malignant cells by image-processing-based segmentation for breast cancer diagnosis is important for early diagnosis. In the present study, Extreme Learning Machine (ELM) classification was performed for 9 features based on image segmentation in the Breast Cancer Wisconsin (Diagnostic) data set in the UC Irvine Machine Learning Repository database. RESULTS: The results obtained with the developed method were compared with the results of other machine learning methods (Naive Bayes, Support Vector Machine, and Artificial Neural Network) and it showed the highest performance, with a result of 98.99%. CONCLUSIONS: It was found that both accuracy and speed were good. We present a method that can be applied in cell morphology detection and classification in automated systems that classify by computer-aided mammogram image features.
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spelling pubmed-61541162018-09-26 Extreme Learning Machine (ELM)-Based Classification of Benign and Malignant Cells in Breast Cancer Toprak, Abdullah Med Sci Monit Lab/In Vitro Research BACKGROUND: Breast cancer is one of the most common cancer types in the world and is a serious threat to health. This type of cancer is complex; it is a hereditary disease and does not result from a single cause. The diagnosis of cancer starts with a biopsy. Various methods are used to detect and recognize cancer cells, from microscopic images and mammography to ultrasonography and magnetic resonance images (MRI). MATERIAL/METHODS: Detection and characterization of benign and malignant cells by image-processing-based segmentation for breast cancer diagnosis is important for early diagnosis. In the present study, Extreme Learning Machine (ELM) classification was performed for 9 features based on image segmentation in the Breast Cancer Wisconsin (Diagnostic) data set in the UC Irvine Machine Learning Repository database. RESULTS: The results obtained with the developed method were compared with the results of other machine learning methods (Naive Bayes, Support Vector Machine, and Artificial Neural Network) and it showed the highest performance, with a result of 98.99%. CONCLUSIONS: It was found that both accuracy and speed were good. We present a method that can be applied in cell morphology detection and classification in automated systems that classify by computer-aided mammogram image features. International Scientific Literature, Inc. 2018-09-17 /pmc/articles/PMC6154116/ /pubmed/30222727 http://dx.doi.org/10.12659/MSM.910520 Text en © Med Sci Monit, 2018 This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) )
spellingShingle Lab/In Vitro Research
Toprak, Abdullah
Extreme Learning Machine (ELM)-Based Classification of Benign and Malignant Cells in Breast Cancer
title Extreme Learning Machine (ELM)-Based Classification of Benign and Malignant Cells in Breast Cancer
title_full Extreme Learning Machine (ELM)-Based Classification of Benign and Malignant Cells in Breast Cancer
title_fullStr Extreme Learning Machine (ELM)-Based Classification of Benign and Malignant Cells in Breast Cancer
title_full_unstemmed Extreme Learning Machine (ELM)-Based Classification of Benign and Malignant Cells in Breast Cancer
title_short Extreme Learning Machine (ELM)-Based Classification of Benign and Malignant Cells in Breast Cancer
title_sort extreme learning machine (elm)-based classification of benign and malignant cells in breast cancer
topic Lab/In Vitro Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6154116/
https://www.ncbi.nlm.nih.gov/pubmed/30222727
http://dx.doi.org/10.12659/MSM.910520
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