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Feature Selection and Classification of Clinical Datasets Using Bioinspired Algorithms and Super Learner
A computer-aided diagnosis (CAD) system that employs a super learner to diagnose the presence or absence of a disease has been developed. Each clinical dataset is preprocessed and split into training set (60%) and testing set (40%). A wrapper approach that uses three bioinspired algorithms, namely,...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Hindawi
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8149240/ https://www.ncbi.nlm.nih.gov/pubmed/34055041 http://dx.doi.org/10.1155/2021/6662420 |