The identification of improvements to the process of release of Blood Glucose test results from a clinical analysis laboratory with the aid of Paraconsistent Annoted Evidential Locig Eτ

Authors

DOI:

https://doi.org/10.33448/rsd-v12i12.44049

Keywords:

Decision-making; Paraconsistent annotated evidential logic Eτ; Blood glucose.

Abstract

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.

References

Abe, J. M. (1992). Fundamentos da lógica anotada. Tese de Doutorado. Programa de Pós-Graduação em Filosofia. Universidade de São Paulo.

Abe, J. M. (2015). Sistemas paraconsistentes baseados em inteligência: Novas tendências nas aplicações de paraconsistência (Vol. 94). Springer.

Abe, J. M., Akama, S., & Nakamatsu, K. (2015). Introduction to Annotated Logics (Vol. 8). Cham: Springer International Publishing.

Abe, J. M., Lopes, H. F. S., & Anghinah, R. (2016). Paraconsistent Neurocomputing and Biological Signals Analysis. In J. M. Abe (Ed.), Paraconsistent Intelligent-Based Systems. Intelligent Systems Reference Library. 94, 273-306. Cham: Springer International Publishing.

Abe, J. M., Silva Filho, J. I., Celestino, U., & Araujo, H. C. (2011). Lógica Paraconsistente Anotada Evidencial Eτ. Comunicar.

Antunes, Y. R., Oliveira, E. M., Pereira, L. A., & Picanço, M. F. P. (2021, dezembro). Diabetes Mellitus Tipo 2: A importância do diagnóstico precoce da diabetes. Brazilian Journal of Development, 7(12), 116526-116551. https://ojs.brazilianjournals.com.br/index.php/BRJD/article/view/41218

Blick, K. E. (1997). Sistemas informáticos laboratoriais de tomada de decisão como ferramentas essenciais para o alcance da qualidade total. Química Clínica, 43 (5), 908-912.

Brutti, B., Flores, J., Hermes, J., Martelli, G., Porto, D. S., & Anversa, E. T. R. (2019, julho/agosto). Diabete Mellitus: definição, diagnóstico, tratamento e mortalidade no Brasil, Rio Grande do Sul e Santa Maria, no período de 2010 a 2014. Brazilian Journal of Health Review, 2(4), 3174-3182. https://ojs.brazilianjournals.com.br/ojs/index.php/BJHR/article/view/2172/2203

Carvalho, F. R., & Abe, J. M. (2011). Tomadas de decisão com ferramentas da lógica paraconsistente anotada – Método Paraconsistente de Decisão – MPD. São Paulo: Blücher, 2011.

Cobas, R. (2015, outubro/dezembro). Diabetes: recordando uma história. Revista do Hospital Universitário Pedro Ernesto, 14 (4), 35-36. https://www.e-publicacoes.uerj.br/index.php/revistahupe/article/view/20069

Dill, R. P., Costa Jr., N., & Santos, A. A. P. (2014). Corporate Profitability Analysis: A Novel Application for Paraconsistent Logic. Applied Mathematical Sciences.

Fiocruz. (2021). Diabetes. https://portal.fiocruz.br/diabetes

Ministério da Saúde. (2006). Diabetes Millitus. https://bvsms.saude.gov.br/bvs/publicacoes/diabetes_mellitus.PDF

Ministério da Saúde. (2023). Diabetes. https://bvsms.saude.gov.br/diabetes

Nakamatsu, K., & Abe, J. M. (2009). The development of paraconsistent annotated logic programs. International Journal of Reasoning-based Intelligent Systems, 1 (1/2), 92.

Orozco, L. B., & Alves, S. H. S. (2017). Diferenças do autocuidado entre pacientes com Diabetes Mellitus Tipo 1 e 2. Psicologia, Saúde e Doenças, 18, (1), 234-247. https://www.redalyc.org/pdf/362/36250481019.pdf

Silva Filho, J. I.., Abe, J. M., & Lambert-Torres, G. (2008). Inteligência Artificial com as Redes de Análises Paraconsistentes. LTC.

Souza, S., & Abe, J. M. (2015). Paraconsistent Artificial Neural Networks and Aspects of Pattern Recognition. In J. M. Abe (Ed.), Paraconsistent Intelligent-Based Systems. Intelligent Systems Reference Library. 94, 207-231. Cham: Springer International Publishing.

Torres, C. R., & Reis, R. (2015). The New Hardware Structure of the Emmy II Robot. In J. M. Abe (Ed.), Paraconsistent Intelligent-Based Systems. Intelligent Systems Reference Library. 94, 87-103. Springer International Publishing.

Yin, R. K, (2015). Estudo de Caso: Planejamento e métodos. Bookman.

Published

18/11/2023

How to Cite

CABRAL, J. R.; ABE, J. M.; BONETTE, L. R. .; LIMA, P. C. de . The identification of improvements to the process of release of Blood Glucose test results from a clinical analysis laboratory with the aid of Paraconsistent Annoted Evidential Locig Eτ . Research, Society and Development, [S. l.], v. 12, n. 12, p. e105121244049, 2023. DOI: 10.33448/rsd-v12i12.44049. Disponível em: https://www.rsdjournal.org/index.php/rsd/article/view/44049. Acesso em: 26 feb. 2024.

Issue

Section

Engineerings