Um Sistema Inteligente para a Avaliação de Risco da DRC e Encaminhamento de Pacientes em Emergência para Unidades de Saúde

• Andressa Carvalho Melo da Silveira UFAL
• Leandro Dias da Silva UFAL
• Álvaro Sobrinho UFAL / UFAPE

DOI: https://doi.org/10.5753/sbcas.2021.16098

Abstract

The high incidence and prevalence of Chronic Kidney Disease (CKD), often caused by late diagnoses, is a critical public health problem. Qualitative and quantitative comparative analyzes were performed, by a systematic literature review and an experiment with machine learning techniques, respectively. The J48 decision tree, with 95.00% accuracy, was used to develop an intelligent system to assess the risk of CKD. In addition, when the patient with CKD is out of his/her municipality and an emergency occurs, the system recommends the patient to attend to an appropriate healthcare facility, depending on the clinical situation, to prevent the late or inadequate healthcare.

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