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Erschienen in:
Diagnosis and Fault-Tolerant Control of Critical Infrastructures Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Supporting Breast Cancer Diagnosis with Multi-objective Genetic Algorithm for Outlier Detection

verfasst von : Agnieszka Duraj, Lukasz Chomatek

Erschienen in: Advanced Solutions in Diagnostics and Fault Tolerant Control

Verlag: Springer International Publishing

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Abstract

Outlier detection in medical data covers a broad spectrum of medical research. In this paper, the authors propose a new approach to outlier detection based on the multi-objective genetic algorithm. In medical data, an outlier may be considered as a deviation which indicates the existence of cancerous cells in the breast. The paper presents the results of tests which were conducted on the set of medical data from the repository. The results of the study indicate that our method can be successfully applied to the medical problem in question.

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Vorheriges Kapitel Identification of Emotions Based on Human Facial Expressions Using a Color-Space Approach
Nächstes Kapitel Nuclei Recognition Using Convolutional Neural Network and Hough Transform
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Metadaten
Titel
Supporting Breast Cancer Diagnosis with Multi-objective Genetic Algorithm for Outlier Detection
verfasst von
Agnieszka Duraj
Lukasz Chomatek
Copyright-Jahr
2018
Buch
Advanced Solutions in Diagnostics and Fault Tolerant Control

Print ISBN: 978-3-319-64473-8

Electronic ISBN: 978-3-319-64474-5

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-319-64474-5_25