A web based expert system for pre-diagnosing gestational diabetes / Ahlam Zaini Ab Rahim
Medical area has a lot of contribution in revealing any particulars about the medicine such as type of disease, implication of a disease and also some prediction of having a disease. This research uses rule^based expert system representation and techniques to solve and make a pre-diagnosis of hav...
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| Format: | Thesis |
| Language: | English |
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2006
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| Online Access: | http://ir.uitm.edu.my/id/eprint/933/ http://ir.uitm.edu.my/id/eprint/933/1/TB_AHLAM%20ZAINI%20AB%20RAHIM%20CS%2006_5%20P01.pdf |
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uitm-933 |
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eprints |
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uitm-9332018-10-30T07:27:53Z http://ir.uitm.edu.my/id/eprint/933/ A web based expert system for pre-diagnosing gestational diabetes / Ahlam Zaini Ab Rahim Ahlam Zaini, Ab Rahim Electronic computers. Computer science Medical area has a lot of contribution in revealing any particulars about the medicine such as type of disease, implication of a disease and also some prediction of having a disease. This research uses rule^based expert system representation and techniques to solve and make a pre-diagnosis of having gestational diabetes (GD) among pregnant women. After several times taken in understanding the domain subject, the researcher listed a set of risk factors and common symptoms, conducted some interviews with some experts in order to get the solution of handling GD and uncertainty management through web-based expert system. Each phase of the research methodology was gone through in order to have and analyze the effectiveness of pre-diagnosing through the web based application. 2006 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/933/1/TB_AHLAM%20ZAINI%20AB%20RAHIM%20CS%2006_5%20P01.pdf Ahlam Zaini, Ab Rahim (2006) A web based expert system for pre-diagnosing gestational diabetes / Ahlam Zaini Ab Rahim. Degree thesis, Universiti Teknologi MARA. |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
Universiti Teknologi MARA |
| building |
UiTM Institutional Repository |
| collection |
Online Access |
| language |
English |
| topic |
Electronic computers. Computer science |
| spellingShingle |
Electronic computers. Computer science Ahlam Zaini, Ab Rahim A web based expert system for pre-diagnosing gestational diabetes / Ahlam Zaini Ab Rahim |
| description |
Medical area has a lot of contribution in revealing any particulars about the medicine
such as type of disease, implication of a disease and also some prediction of having a
disease. This research uses rule^based expert system representation and techniques to
solve and make a pre-diagnosis of having gestational diabetes (GD) among pregnant
women. After several times taken in understanding the domain subject, the researcher
listed a set of risk factors and common symptoms, conducted some interviews with some
experts in order to get the solution of handling GD and uncertainty management through
web-based expert system. Each phase of the research methodology was gone through in
order to have and analyze the effectiveness of pre-diagnosing through the web based
application. |
| format |
Thesis |
| author |
Ahlam Zaini, Ab Rahim |
| author_facet |
Ahlam Zaini, Ab Rahim |
| author_sort |
Ahlam Zaini, Ab Rahim |
| title |
A web based expert system for pre-diagnosing gestational diabetes / Ahlam Zaini Ab Rahim |
| title_short |
A web based expert system for pre-diagnosing gestational diabetes / Ahlam Zaini Ab Rahim |
| title_full |
A web based expert system for pre-diagnosing gestational diabetes / Ahlam Zaini Ab Rahim |
| title_fullStr |
A web based expert system for pre-diagnosing gestational diabetes / Ahlam Zaini Ab Rahim |
| title_full_unstemmed |
A web based expert system for pre-diagnosing gestational diabetes / Ahlam Zaini Ab Rahim |
| title_sort |
web based expert system for pre-diagnosing gestational diabetes / ahlam zaini ab rahim |
| publishDate |
2006 |
| url |
http://ir.uitm.edu.my/id/eprint/933/ http://ir.uitm.edu.my/id/eprint/933/1/TB_AHLAM%20ZAINI%20AB%20RAHIM%20CS%2006_5%20P01.pdf |
| first_indexed |
2023-09-18T22:45:13Z |
| last_indexed |
2023-09-18T22:45:13Z |
| _version_ |
1777417178896662528 |