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espanolSe propone un metodo predictivo para detectar el cancer de mama, basado en las siguientes variables: edad, peso, talla, indice de masa corporal, escolaridad, estrato socioeconomico, seguridad social, fumador, cuando dejo de fumar, fumador pasivo, consume licor, cantidad de licor, herencia familiar de cancer, edad de la menarca, menopausia, embarazos, partos, edad del primer parto, lactancia, consumo de anticonceptivos orales, cuanto anos consumio anticonceptivos orales, tiempo de suspension de anticonceptivos orales, terapia de reemplazo hormonal y presencia del gen GSTM1. Tomando como referencias pacientes de la region central de Colombia (Caldas), se definieron dos bases de datos, una de personas sin cancer y otra de personas con cancer. La misma base de datos de entrenamiento fue empleada para prueba. La metodologia propuesta, define y entrena un sistema de clasificacion bayesiano, con una base de datos de pacientes con cancer y sin cancer. Posteriormente, se realiza una validacion del sistema con el fin de determinar el numero de aciertos y errores en el reconocimiento de esta enfermedad. Como resultado, se logra un porcentaje de aciertos del 100%. EnglishWe propose a predictive method to detect breast cancer, based on the following variables: Age, weight, height, body mass index, schooling, socioeconomic stratum, social security, smoker, when quit smoking, passive smoker, consumption of liquor, quantity of liquor, family inheritance of cancer, age of menarche, menopause, pregnancies, age of first birth, breastfeeding, consumption of oral contraceptives, how many years of oral contraceptive use, oral contraceptive suspension time, hormone replacement therapy, and the presence of the GSTM1 gene. Taking as reference patients from the central region of Colombia (Caldas), two databases were defined, one of people without cancer and another of people with cancer. The same training database was used for testing. The proposed methodology defines and trains a Bayesian classification system, with a database of patients with cancer and without cancer. Subsequently, a system validation is performed in order to determine the number of successes and errors in the recognition of this disease. As a result, a 100% success rate is achieved.

Sistema Predictivo Bayesiano para Detección del Cáncer de Mama