Machine Learning and Feature Selection Applied to SEER Data to Reliably Assess Thyroid Cancer Prognosis

Utilizing historical clinical datasets to guide future treatment choices is beneficial for patients and physicians. Machine learning and feature selection algorithms (namely, Fisher’s discriminant ratio, Kruskal-Wallis’ analysis, and Relief-F) have been combined in this research to analyse a SEER da...

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Detalles Bibliográficos
Autores principales: Mourad, Moustafa, Moubayed, Sami, Dezube, Aaron, Mourad, Youssef, Park, Kyle, Torreblanca-Zanca, Albertina, Torrecilla, José S., Cancilla, John C., Wang, Jiwu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083829/
https://www.ncbi.nlm.nih.gov/pubmed/32198433
http://dx.doi.org/10.1038/s41598-020-62023-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7083829/
https://www.ncbi.nlm.nih.gov/pubmed/32198433
http://dx.doi.org/10.1038/s41598-020-62023-w

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