(untitled) (Research, Society and Development, 2023)
The process of conducting tests in a clinical laboratory goes through different stages. For the most part, it is automated, but data discrepancies require interruptions for human decision-making. Such interruptions delay the results and impact medical decisions. If we consider that one of these diagnoses is diabetes, there is a worsening of the situation. Based on this issue, the objective of this work is to propose an improvement in the process of releasing the results of laboratory tests through the application of Paraconsistent Annotated Evidential Logic Eτ and the Para-Analyzer algorithm. This process aims to enable the professionals involved in these stages to develop decision-making more quickly. As a specific focus, the research used the detection of blood glucose levels, a test performed to confirm a diagnosis of diabetes. In the theoretical depth of the study, questions about Diabetes Mellitus (DM) and Paraconsistent Annotated Evidential Logic Eτ were raised. As a methodological process, two phases were used. In the first phase, a survey of common sensitive points in this type of test was conducted. Then, this data was associated with the blood glucose evaluation flow in a clinical laboratory and applied through the Para-Analyzer algorithm using Paraconsistent Annotated Evidential Logic Eτ. From this, a model was presented to assist biomedical professionals in their decision-making, seeking a faster and more reliable release of results for patients. As a secondary result, it was also possible to perceive that Paraconsistent Annotated Evidential Logic Eτ can be applied in other areas of healthcare, providing an option for process improvement in general.