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https://hdl.handle.net/1822/76501
Título: | Cluster analysis for breast cancer patterns identification |
Autor(es): | Azevedo, Beatriz Flamia Alves, Filipe Rocha, Ana Maria A. C. Pereira, Ana I. |
Palavras-chave: | Breast cancer Cluster analysis Disease diagnosis |
Data: | 2021 |
Editora: | Springer |
Revista: | Communications in Computer and Information Science |
Citação: | Azevedo B.F., Alves F., Rocha A.M.A.C., Pereira A.I. (2021) Cluster Analysis for Breast Cancer Patterns Identification. In: Pereira A.I. et al. (eds) Optimization, Learning Algorithms and Applications. OL2A 2021. Communications in Computer and Information Science, vol 1488. Springer, Cham. https://doi.org/10.1007/978-3-030-91885-9_37 |
Resumo(s): | Safety in patient decision-making is one of the major health care challenges. Computational support in establishing diagnoses and preventing errors will contribute to an enhancement in doctor-patient communication. This work performs a three-dimensional cluster analysis, using k-means algorithm, to identify patterns in a breast cancer database. The methodology proposed can be useful to identify patterns in the database that are normally difficult to be noted by classical methods, such as statistical methods. The three-dimensional cluster approach was explored combining three variables at once. The k-means algorithm is used to recognize the hidden patterns on the database. Sub-clusters are used to separate the benign and malignant tumors inside the global cluster. The results present effective analyses of three different clusters based on different combinations between variables. Thus, health professionals can obtain a better understanding of the properties of different types of tumor, identifying the mined abstract tumor features, through the cluster data analysis. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/76501 |
ISBN: | 9783030918842 |
DOI: | 10.1007/978-3-030-91885-9_37 |
ISSN: | 1865-0929 |
Versão da editora: | https://link.springer.com/chapter/10.1007/978-3-030-91885-9_37 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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OL2A_Clustering_algorithms_and_Applications.pdf | 607,54 kB | Adobe PDF | Ver/Abrir |