JP Journal of Biostatistics

The JP Journal of Biostatistics is a highly regarded open-access international journal indexed in the Emerging Sources Citation Index (ESCI). It focuses on the application of statistical theory and methods in resolving problems in biological, biomedical, and agricultural sciences. The journal encourages the submission of experimental papers that employ relevant algorithms and also welcomes survey articles in the fields of biostatistics and epidemiology.

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ENHANCED DENGUE DETECTION AND CONTROL USING A FUZZY EXPERT SYSTEM IN ENDEMIC REGIONS

Authors

  • Muhammad Saleem
  • Saadia Malik
  • Muhammad Hamid
  • Mohammed Aman

Keywords:

artificial intelligence in medicine, disease detection, dengue fever, fuzzy sets, fuzzy inference system

DOI:

https://doi.org/10.17654/0973514325012

Abstract

This paper proposes an expert system for detecting dengue using a fuzzy logic approach in Pakistan. A knowledge-based system represents an expert system, which is one of the most frequent types of Artificial Intelligence in Medicine (AIM), with medical knowledge of a clearly defined goal and the ability to reach the correct conclusion. In a proposed system, the knowledge of a particular issue is typically represented by a set of rules rather than individual variables. Through mosquito bites an infected mosquito transmits the dengue virus that functions as a pathogen exclusively in human bodies. Dengue fever is an infectious tropical disease. The risk of dying from dengue fever increases when the diagnosis is delayed, despite the fact that only a small fraction of people infected with the disease actually develop severe symptoms. Because of this, it is essential to diagnose dengue fever in its earliest stages. As a result, the main purpose of this research was to construct an expert system for the early detection of dengue disease utilizing the Fuzzy Inference System (FIS), a potent instrument for coping with imprecision and uncertainty. The system takes a patient’s physical symptoms as input and translates them into fuzzy membership functions for analysis. The system that was designed can be used to assist a patient in receiving an early diagnosis of dengue disease. The proposed system has been tested on real data sets and achieved a remarkable accuracy rate of 96%.

Received: December 4, 2024
Accepted: February 14, 2025

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Published

2025-03-26

Issue

Vol. 25 No. 2 (2025)

Section

Articles

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Copyright (c) 2025 PUSHPA PUBLISHING HOUSE, PRAYAGRAJ, INDIA

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How to Cite

ENHANCED DENGUE DETECTION AND CONTROL USING A FUZZY EXPERT SYSTEM IN ENDEMIC REGIONS. (2025). JP Journal of Biostatistics, 25(2), 243-258. https://doi.org/10.17654/0973514325012

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