Knowledge in Medical Prescriptions with the Help of Genetic Fuzzy Hybrid Model

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Published Dec 15, 2023
https://doi.org/10.56158/jpte.2023.51.2.02
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Vol. 2 No. 02 (2023): December

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Bahareh Tadayoni
Department of Computer Engineering, Lar University, Lar, Iran
https://orcid.org/0009-0001-0345-9277
Ehsan Amiri
Department of Computer Engineering, Jahrom Branch, Jahrom University, Jahrom, Iran,
https://orcid.org/0000-0001-6058-7083
Faezeh Soorani
Department of Computer Engineering, Jahrom Branch, Jahrom University, Jahrom, Iran,
https://orcid.org/0009-0008-2735-2635

Abstract

Following the progress made in the construction of high-speed processors, the limiting effect of the way data is entered into the computer on the speed of information transfer has become more apparent. By using processing devices, in addition to achieving higher speed in the data retrieval stage, it is also possible to use their pre-processing capabilities and change the data format. Considering the importance of the topic and the work that has been done in this field, the need to discover the knowledge of the existing features with the help of choosing the appropriate feature for the classification of texts is well felt. In this article, genetic algorithm and fuzzy logic have been used to present a method for classifying texts in insurance booklets. This system is based on several stages. These steps include the learning phase that examines a set of educational texts to extract the characteristics of the categories to be the characteristics of each category; the test phase of the system is used to classify uncategorized texts. The proposed method's accuracy has been assessed using a collection of patient notebooks, and the outcomes indicate an accuracy of around 98% for the classification.

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Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite
Tadayoni, B., Amiri, E., & Soorani, F. (2023). Knowledge in Medical Prescriptions with the Help of Genetic Fuzzy Hybrid Model. International Journal of Pioneering Technology and Engineering, 2(02), 142–146. https://doi.org/10.56158/jpte.2023.51.2.02

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