Modelo de predicción para la detención de anemia en adultos mayores utilizando minería de datos

Abstract

The purpose of this research is to design a predictive model using data mining to detect cases of anemia in older adults. To achieve this, the activities of each of the phases of the KDD (Knowledge Discovery in Databases) methodology were employed. An exhaustive study of the bibliographic review on topics related to data mining was carried out to obtain a clear view of the different methodologies, tools, and techniques for detecting diseases through analysis. For the prediction of anemia cases, some variables such as hemoglobin levels, BMI, age, and other factors associated with anemia were considered. Once the model was designed, the testing stage was carried out where previously collected data sets from older adults were used. These data were used to train the model and adjust its parameters so that it could make accurate predictions. The results obtained allowed the evaluation of the model's effectiveness in detecting anemia and laid the foundation for future research in this field.