Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar
The problem in most of the clinics around the world is the procedure of the patient to see the doctor. Patient need to register, queuing and this will consuming time. A Mobile Fever Diagnosis Expert System (MFDES) is developed to reduce the waiting time of the patient to see doctor for a treatment....
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| Format: | Thesis |
| Language: | English |
| Published: |
2014
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| Online Access: | https://ir.uitm.edu.my/id/eprint/32715/ |
| _version_ | 1848808095505973248 |
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| author | Mohd Nashrullah, Zulfakar |
| author_facet | Mohd Nashrullah, Zulfakar |
| author_sort | Mohd Nashrullah, Zulfakar |
| building | UiTM Institutional Repository |
| collection | Online Access |
| description | The problem in most of the clinics around the world is the procedure of the patient to see the doctor. Patient need to register, queuing and this will consuming time. A Mobile Fever Diagnosis Expert System (MFDES) is developed to reduce the waiting time of the patient to see doctor for a treatment. The scope of this MFDES is for two type of fever that was the normal fever and dengue fever. This research has conducted in the Unit Kesihatan (UK) UiTM Seri Iskandar Perak. This MFDES was developed in android platform using the Visual Basic Language Programming. The MFDES is implemented through the rule-based expert system rule using IF THEN rule. The MFDES is able to diagnose fever based on the symptoms given in the system and provide recommendation of the medicine depending on disease. The results from this project MFDES has reduce time that doctor take to diagnose patient if the patient disease was fever type. The MFDES can be enhanced by adding more function, adding more type of fever and developed it into another programming language. Summary of MFDES based on finding and analysis show that MFDES diagnose faster than the manual diagnose. |
| first_indexed | 2025-11-14T22:53:16Z |
| format | Thesis |
| id | uitm-32715 |
| institution | Universiti Teknologi MARA |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T22:53:16Z |
| publishDate | 2014 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uitm-327152020-07-21T03:48:26Z https://ir.uitm.edu.my/id/eprint/32715/ Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar Mohd Nashrullah, Zulfakar Neural Networks (Computer). Artificial intelligence Cell phones The problem in most of the clinics around the world is the procedure of the patient to see the doctor. Patient need to register, queuing and this will consuming time. A Mobile Fever Diagnosis Expert System (MFDES) is developed to reduce the waiting time of the patient to see doctor for a treatment. The scope of this MFDES is for two type of fever that was the normal fever and dengue fever. This research has conducted in the Unit Kesihatan (UK) UiTM Seri Iskandar Perak. This MFDES was developed in android platform using the Visual Basic Language Programming. The MFDES is implemented through the rule-based expert system rule using IF THEN rule. The MFDES is able to diagnose fever based on the symptoms given in the system and provide recommendation of the medicine depending on disease. The results from this project MFDES has reduce time that doctor take to diagnose patient if the patient disease was fever type. The MFDES can be enhanced by adding more function, adding more type of fever and developed it into another programming language. Summary of MFDES based on finding and analysis show that MFDES diagnose faster than the manual diagnose. 2014-01-26 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/32715/1/32715.pdf Mohd Nashrullah, Zulfakar (2014) Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar. (2014) Degree thesis, thesis, Universiti Teknologi MARA Cawangan Perak. <http://terminalib.uitm.edu.my/32715.pdf> |
| spellingShingle | Neural Networks (Computer). Artificial intelligence Cell phones Mohd Nashrullah, Zulfakar Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar |
| title | Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar |
| title_full | Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar |
| title_fullStr | Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar |
| title_full_unstemmed | Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar |
| title_short | Mobile fever diagnosis expert system / Mohd Nashrullah Zulfakar |
| title_sort | mobile fever diagnosis expert system / mohd nashrullah zulfakar |
| topic | Neural Networks (Computer). Artificial intelligence Cell phones |
| url | https://ir.uitm.edu.my/id/eprint/32715/ |