Modelagem Fuzzy para o diagnóstico de Lúpus

Abstract

The present Bachelor's Thesis aims to comprehend the manifestations of Systemic Lupus Erythematosus (SLE) and introduces mathematical models to analyze clinical, laboratory, and immunological manifestations, with the goal of achieving an effective and early diagnosis. Hypothetical simulations for lupus cases are conducted, emphasizing the importance of prompt diagnosis. The mathematical modeling, employing Fuzzy Rule-Based Systems, calculates the probability for lupus diagnosis, highlighting the significance of considering the levels of each symptom and incorporating Antinuclear Antibodies (ANA) as an input variable for diagnosis, rather than an exclusion criterion in negative cases. This approach enables early diagnosis and the initiation of treatments against lupus, given its exponential potential for clinical complications. Finally, the study underscores the need for regular medical examinations and monitoring of the population, along with ongoing research on new diagnostic methods, aiming to reduce mortality among individuals with the disease.