Diagnosis and treatment of Guillain-Barre using the prolog expert system

Laberiano Andrade-Arenas, Pedro Molina-Velarde, Félix Pucuhuayla-Revatta, Cesar Yactayo-Arias

Producción científica: Artículo CientíficoArtículo originalrevisión exhaustiva


This research is mostly about Guillain-Barre syndrome (GBS), a complicated neurological condition with many subtypes that make diagnosis and treatment hard, even though medical care is always getting better. The main goal of this study is to build and test an expert system that can correctly diagnose these subtypes, with a focus on early detection and personalized treatments. The evaluation of the system was carried out using a dataset composed of 20 cases (12 positive and 8 negative). A confusion matrix was used to evaluate key metrics such as precision, sensitivity, and specificity. The findings demonstrate precision and sensitivity of 83% and specificity of 75%. These findings unambiguously demonstrate the efficacy of the system in correctly identifying positive Guillain-Barre cases while substantially reducing false negatives. In conclusion, this expert system offers a potentially useful tool to improve the accuracy of the diagnosis and treatment of Guillain-Barre patients. However, to take advantage of its full potential in clinical practice, it should be used as diagnostic support and not replace the medical staff, and it should be updated periodically to reflect new findings in medicine.

Idioma originalInglés estadounidense
Páginas (desde-hasta)333-342
PublicaciónIndonesian Journal of Electrical Engineering and Computer Science
EstadoIndizado - ene. 2024

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© 2024 Institute of Advanced Engineering and Science. All rights reserved.


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