Publications

@article{porto-alvarez_ct-based_2023,

title = {CT-based radiomics to predict KRAS mutation in CRC patients using a machine learning algorithm: a retrospective study},

author = {Jacobo Porto-Álvarez and Eva Cernadas and Rebeca Aldaz Martínez and Manuel Fernández-Delgado and Emilio Huelga Zapico and Víctor González-Castro and Sandra Baleato-González and Roberto García-Figueiras and J Ramon Antúnez-López and Miguel Souto-Bayarri},

url = {https://www.mdpi.com/2227-9059/11/8/2144},

year  = {2023},

date = {2023-01-01},

journal = {Biomedicines},

volume = {11},

number = {8},

pages = {2144},

abstract = {This study examines the use of CT-based radiomics to predict KRAS mutations in colorectal cancer (CRC) patients. Several classifiers were tested, with AdaBoost on clinical data achieving the highest accuracy (76.8%). Texture descriptors also showed a correlation with KRAS mutations. Radiomics could reduce the need for invasive diagnostic methods for CRC in the future.},

note = {Publisher: MDPI},

keywords = {colorectal cancer, KRAS Mutation, Radiogenomics, Radiomics, texture analysis},

pubstate = {published},

tppubtype = {article}

}