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

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...

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Main Author:	Che Ros, Shahrul Razhi
Format:	Thesis
Language:	English
Published:	2017
Subjects:	Electronic Computers Computer Science Computer software Software measurement Neural networks (Computer science) Fuzzy logic
Online Access:	https://ir.uitm.edu.my/id/eprint/69577/1/69577.pdf
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id	my-uitm-ir.69577
record_format	uketd_dc
spelling	my-uitm-ir.695772022-11-02T03:23:58Z Early dengue diagnosis based on fuzzy logic / Shahrul Razhi Che Ros 2017-01 Che Ros, Shahrul Razhi 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 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 2017-01 Thesis https://ir.uitm.edu.my/id/eprint/69577/ https://ir.uitm.edu.my/id/eprint/69577/1/69577.pdf text en public degree Universiti Teknologi MARA, Terengganu Faculty of Computer and Mathematical Sciences Wan Abdul Manan, Wan Dorishah
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Wan Abdul Manan, Wan Dorishah
topic	Electronic Computers Computer Science Electronic Computers Computer Science Computer software Electronic Computers Computer Science Software measurement Neural networks (Computer science) Electronic Computers Computer Science Fuzzy logic
spellingShingle	Electronic Computers Computer Science Electronic Computers Computer Science Computer software Electronic Computers Computer Science Software measurement Neural networks (Computer science) Electronic Computers Computer Science Fuzzy logic Che Ros, Shahrul Razhi Early dengue diagnosis based on fuzzy logic / Shahrul Razhi Che Ros
description	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
format	Thesis
qualification_level	Bachelor degree
author	Che Ros, Shahrul Razhi
author_facet	Che Ros, Shahrul Razhi
author_sort	Che Ros, Shahrul Razhi
title	Early dengue diagnosis based on fuzzy logic / Shahrul Razhi Che Ros
title_short	Early dengue diagnosis based on fuzzy logic / Shahrul Razhi Che Ros
title_full	Early dengue diagnosis based on fuzzy logic / Shahrul Razhi Che Ros
title_fullStr	Early dengue diagnosis based on fuzzy logic / Shahrul Razhi Che Ros
title_full_unstemmed	Early dengue diagnosis based on fuzzy logic / Shahrul Razhi Che Ros
title_sort	early dengue diagnosis based on fuzzy logic / shahrul razhi che ros
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2017
url	https://ir.uitm.edu.my/id/eprint/69577/1/69577.pdf
_version_	1783735894061088768

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

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