Early dengue diagnosis based on fuzzy logic / Shahrul Razhi Che Ros

• Main Author: Che Ros, Shahrul Razhi
• Format: Thesis
• Language: English
• Published: 2017
• Subjects: Electronic Computers. Computer Science; Evolutionary programming (Computer science). Genetic algorithms; Computer software; Expert systems (Computer science). Fuzzy expert systems; Software measurement; Neural networks (Computer science); Artificial immune systems. Immunocomputers; Fuzzy logic
• Online Access: https://ir.uitm.edu.my/id/eprint/69577/1/69577.pdf; https://ir.uitm.edu.my/id/eprint/69577/

Dengue is a potentially high-risk vector borne disease that spread by the female aedes Aegypti mosquitoes. WHO in their report said that the dengue has become a global burden nowadays. Many cases have been report all over the world. The incidence of dengue has grown dramatically around the world in recent decades. The main goals of this project is study how the dengue is diagnose by a doctor and to create a system that can help to detect this disease from the early based on its symptoms. Due to this situation, an expert system using fuzzy logic are proposed. The system are design to perform a calculation based on the specific data that has been collected form the expertise. At the end, an expert system based on fuzzy logic has been successfully develop and tested and for the result, this project has archive 66.67% in the accuracy test with the expert from medical field. So, by having this expert system, we hope that by the it a bit can help to control this disease from widely spread without any preventions