Robust Estimation of Breast Cancer Incidence Risk in Presence of Incomplete or Inaccurate Information

PURPOSE: To evaluate the robustness of multiple machine learning classifiers for breast cancer risk estimation in the presence of incomplete or inaccurate information. DATA AND METHODS: Open data for this study was obtained from the BCSC Data Resource (http://breastscreening.cancer.gov/). We conduct...

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Detalles Bibliográficos
Autores principales: Kakileti, Siva Teja, Manjunath, Geetha, Dekker, Andre, Wee, Leonard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: West Asia Organization for Cancer Prevention 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7771951/
https://www.ncbi.nlm.nih.gov/pubmed/32856859
http://dx.doi.org/10.31557/APJCP.2020.21.8.2307

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7771951/
https://www.ncbi.nlm.nih.gov/pubmed/32856859
http://dx.doi.org/10.31557/APJCP.2020.21.8.2307

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