Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/50532
Título: | Treating colon cancer survivability prediction as a classification problem |
Autor(es): | Silva, Ana Paula Pinto da Oliveira, Tiago José Martins Neves, José Novais, Paulo |
Palavras-chave: | Colon cancer Prediction Machine learning |
Data: | 2016 |
Editora: | Ediciones Universidad de Salamanca |
Revista: | ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal |
Resumo(s): | This work presents a survivability prediction model for colon cancer developed with machine learning techniques. Survivability was viewed as a classification task where it was necessary to determine if a patient would survive each of the five years following treatment. The model was based on the SEER dataset which, after preprocessing, consisted of 38,592 records of colon cancer patients. Six features were extracted from a feature selection process in order to construct the model. This model was compared with another one with 18 features indicated by a physician. The results show that the performance of the sixfeature model is close to that of the model using 18 features, which indicates that the first may be a good compromise between usability and performance. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/50532 |
DOI: | 10.14201/ADCAIJ2016513750 |
ISSN: | 2255-2863 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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Treating Colon Cancer Survivability Prediction as a Classification Problem.pdf | 283,95 kB | Adobe PDF | Ver/Abrir |