Skin diseases diagnosis support system using fuzzy logic

Nornadzirah Hafizah, Abdullah (2019) Skin diseases diagnosis support system using fuzzy logic. Faculty of Computer System & Software Engineering, Universiti Malaysia Pahang.

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There are many types of skin diseases and difficult to identify the categories of skin diseases. Skin diseases can easily get affected by all different ages either children or adults. There are many types of skin disease include lupus, acne, psoriasis, eczema and impetigo. However, this research only focuses on one type of skin disease only which is eczema. Based on the research that has been conducted, there are many previous researchers use image processing method to determine the skin diseases. The image processing requires more time to learn and need a large space of memory to install the software. Other than that, image processing also requires a high quality of camera or any devices to capture an image to get the accurate result. To buy the devices is costing and not all public users afford to buy it. Thus, this research has purposed a system to identify the type of eczema skin diseased based on factors such as skin irritation, skin condition, location of affection and family history The conceptual model also has been proposed as a logical diagram to show the system work. The conceptual model is based on diagnostic rules. The conceptual model and rules has been tested by using user knowledge improvement before and after using the proposed solution. The test that has been conducted not involved with rules verification because of attire constraint to meet with the dermatologist. The user knowledge tested show that the knowledge of user is increase about eczema compared to before they used the proposed solution. Thus, the proposed solution gave benefit to public user to understand their skin disease diseases and earlier treatment that possible they can applied.

Item Type: Undergraduates Project Papers
Additional Information: Project Paper (Bachelors of Computer Science (Computer Systems & Networking)) -- Universiti Malaysia Pahang – 2018, SV: DR. NOORHUZAIMI@KARIMAH BINTI MOHD NOOR, e-Thesis
Uncontrolled Keywords: Skin diseases; image processing; diagnostic rules; fuzzy logic
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Mrs. Sufarini Mohd Sudin
Date Deposited: 13 Dec 2019 01:54
Last Modified: 13 Dec 2019 01:54
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