Breast cancer prediction with transcriptome profiling using feature selection and machine learning methods

BACKGROUND: We used a hybrid machine learning systems (HMLS) strategy that includes the extensive search for the discovery of the most optimal HMLSs, including feature selection algorithms, a feature extraction algorithm, and classifiers for diagnosing breast cancer. Hence, this study aims to obtain...

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Detalles Bibliográficos
Autores principales: Taghizadeh, Eskandar, Heydarheydari, Sahel, Saberi, Alihossein, JafarpoorNesheli, Shabnam, Rezaeijo, Seyed Masoud
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9526906/
https://www.ncbi.nlm.nih.gov/pubmed/36183055
http://dx.doi.org/10.1186/s12859-022-04965-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9526906/
https://www.ncbi.nlm.nih.gov/pubmed/36183055
http://dx.doi.org/10.1186/s12859-022-04965-8

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