Skin diseases diagnosis support system using fuzzy logic

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 onl...

Full description

Bibliographic Details
Main Author:	Nornadzirah Hafizah, Abdullah
Format:	Undergraduates Project Papers
Language:	English
Published:	2019
Subjects:	QA75 Electronic computers. Computer science QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/26880/ http://umpir.ump.edu.my/id/eprint/26880/ http://umpir.ump.edu.my/id/eprint/26880/1/Skin%20diseases%20diagnosis%20support%20system%20using%20fuzzy.pdf

id	ump-26880
recordtype	eprints
spelling	ump-268802019-12-13T01:54:26Z http://umpir.ump.edu.my/id/eprint/26880/ Skin diseases diagnosis support system using fuzzy logic Nornadzirah Hafizah, Abdullah QA75 Electronic computers. Computer science QA76 Computer software 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. 2019-12 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/26880/1/Skin%20diseases%20diagnosis%20support%20system%20using%20fuzzy.pdf Nornadzirah Hafizah, Abdullah (2019) Skin diseases diagnosis support system using fuzzy logic. Faculty of Computer System & Software Engineering, Universiti Malaysia Pahang. http://fypro.ump.edu.my/ethesis/index.php
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA75 Electronic computers. Computer science QA76 Computer software
spellingShingle	QA75 Electronic computers. Computer science QA76 Computer software Nornadzirah Hafizah, Abdullah Skin diseases diagnosis support system using fuzzy logic
description	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.
format	Undergraduates Project Papers
author	Nornadzirah Hafizah, Abdullah
author_facet	Nornadzirah Hafizah, Abdullah
author_sort	Nornadzirah Hafizah, Abdullah
title	Skin diseases diagnosis support system using fuzzy logic
title_short	Skin diseases diagnosis support system using fuzzy logic
title_full	Skin diseases diagnosis support system using fuzzy logic
title_fullStr	Skin diseases diagnosis support system using fuzzy logic
title_full_unstemmed	Skin diseases diagnosis support system using fuzzy logic
title_sort	skin diseases diagnosis support system using fuzzy logic
publishDate	2019
url	http://umpir.ump.edu.my/id/eprint/26880/ http://umpir.ump.edu.my/id/eprint/26880/ http://umpir.ump.edu.my/id/eprint/26880/1/Skin%20diseases%20diagnosis%20support%20system%20using%20fuzzy.pdf
first_indexed	2023-09-18T22:42:08Z
last_indexed	2023-09-18T22:42:08Z
_version_	1777416985192169472

Skin diseases diagnosis support system using fuzzy logic

Similar Items