TY  - JOUR 
AU  - Escuela de Ingenierias Industrial, Informática y Aeroespacial
AU  - Cueto López, Nahum
AU  - García Ordás, María Teresa
AU  - Vitelli Storelli, Facundo Ezequiel
AU  - Fernández Navarro, Pablo
AU  - Palazuelos Calderón, Camilo
AU  - Alaiz Rodríguez, Rocío
AU  - Ingenieria de Sistemas y Automatica
DA  - 2021/10/10
UR  - https://hdl.handle.net/10612/21276
AB  - [EN] This study evaluates several feature ranking techniques together with some classifiers based on machine learning to identify relevant factors regarding the probability of contracting breast cancer and improve the performance of risk prediction...
LA  - eng
PB  - MDPI
KW  - Ingeniería de sistemas
KW  - Medicina. Salud
KW  - Breast cancer
KW  - Risk prediction model
KW  - Feature selection
KW  - Stability
TI  - Evaluation of Feature Selection Techniques for Breast Cancer Risk Prediction
DO  - 10.3390/ijerph182010670
T2  - International Journal of Environmental Research and Public Health
VL  - 18
M2  - 10670
ER  -