A novel dengue fever (DF) and dengue haemorrhagic fever (DHF) analysis using artificial neural network (ANN)
Dengue fever (DF) is an acute febrile viral disease frequently presented with headache, bone or joint and muscular pains, and rash. A significant percentage of DF patients develop a more severe form of disease, known as dengue haemorrhagic fever (DHF). DHF is the complication of DF. The main pathoph...
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| Format: | Article |
| Language: | English |
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2005
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| Online Access: | http://eprints.um.edu.my/9322/1/A_novel_dengue_fever_%28DF%29_and_dengue_haemorrhagic_fever_%28DHF%29_analysis_using_artificial_neural_network_%28ANN%29.pdf |
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| author | Ibrahim, F. Taib, M.N. Wan Abas, W.A.B. Guan, C.C. Sulaiman, S. |
| author_facet | Ibrahim, F. Taib, M.N. Wan Abas, W.A.B. Guan, C.C. Sulaiman, S. |
| author_sort | Ibrahim, F. |
| collection | UM |
| description | Dengue fever (DF) is an acute febrile viral disease frequently presented with headache, bone or joint and muscular pains, and rash. A significant percentage of DF patients develop a more severe form of disease, known as dengue haemorrhagic fever (DHF). DHF is the complication of DF. The main pathophysiology of DHF is the development of plasma leakage from the capillary, resulting in haemoconcentration, ascites, and pleural effusion that may lead to shock following defervescence of fever. Therefore, accurate prediction of the day of defervescence of fever is critical for clinician to decide on patient management strategy. To date, no known literature describes of any attempt to predict the day of defervescence of fever in DF patients. This paper describes a non-invasive prediction system for predicting the day of defervescence of fever in dengue patients using artificial neural network. The developed system bases its prediction solely on the clinical symptoms and signs and uses the multilayer feed-forward neural networks (MFNN). The results show that the proposed system is able to predict the day of defervescence in dengue patients with 90 prediction accuracy. © 2005 Elsevier Ireland Ltd. All rights reserved. |
| first_indexed | 2024-03-06T05:23:33Z |
| format | Article |
| id | um.eprints-9322 |
| institution | Universiti Malaya |
| language | English |
| last_indexed | 2024-03-06T05:23:33Z |
| publishDate | 2005 |
| record_format | dspace |
| spelling | um.eprints-93222018-08-09T08:58:27Z http://eprints.um.edu.my/9322/ A novel dengue fever (DF) and dengue haemorrhagic fever (DHF) analysis using artificial neural network (ANN) Ibrahim, F. Taib, M.N. Wan Abas, W.A.B. Guan, C.C. Sulaiman, S. T Technology (General) TA Engineering (General). Civil engineering (General) Dengue fever (DF) is an acute febrile viral disease frequently presented with headache, bone or joint and muscular pains, and rash. A significant percentage of DF patients develop a more severe form of disease, known as dengue haemorrhagic fever (DHF). DHF is the complication of DF. The main pathophysiology of DHF is the development of plasma leakage from the capillary, resulting in haemoconcentration, ascites, and pleural effusion that may lead to shock following defervescence of fever. Therefore, accurate prediction of the day of defervescence of fever is critical for clinician to decide on patient management strategy. To date, no known literature describes of any attempt to predict the day of defervescence of fever in DF patients. This paper describes a non-invasive prediction system for predicting the day of defervescence of fever in dengue patients using artificial neural network. The developed system bases its prediction solely on the clinical symptoms and signs and uses the multilayer feed-forward neural networks (MFNN). The results show that the proposed system is able to predict the day of defervescence in dengue patients with 90 prediction accuracy. © 2005 Elsevier Ireland Ltd. All rights reserved. 2005 Article PeerReviewed application/pdf en http://eprints.um.edu.my/9322/1/A_novel_dengue_fever_%28DF%29_and_dengue_haemorrhagic_fever_%28DHF%29_analysis_using_artificial_neural_network_%28ANN%29.pdf Ibrahim, F. and Taib, M.N. and Wan Abas, W.A.B. and Guan, C.C. and Sulaiman, S. (2005) A novel dengue fever (DF) and dengue haemorrhagic fever (DHF) analysis using artificial neural network (ANN). Computer Methods and Programs in Biomedicine, 79 (3). pp. 273-281. ISSN 01692607, DOI https://doi.org/10.1016/j.cmpb.2005.04.002 <https://doi.org/10.1016/j.cmpb.2005.04.002>. http://www.scopus.com/inward/record.url?eid=2-s2.0-23944451153&partnerID=40&md5=f4774e2ce36fc1a092a6cfd66d78e672 www.sciencedirect.com/science/article/pii/S0169260705000866 http://www.ncbi.nlm.nih.gov/pubmed/15925426 10.1016/j.cmpb.2005.04.002 |
| spellingShingle | T Technology (General) TA Engineering (General). Civil engineering (General) Ibrahim, F. Taib, M.N. Wan Abas, W.A.B. Guan, C.C. Sulaiman, S. A novel dengue fever (DF) and dengue haemorrhagic fever (DHF) analysis using artificial neural network (ANN) |
| title | A novel dengue fever (DF) and dengue haemorrhagic fever (DHF) analysis using artificial neural network (ANN) |
| title_full | A novel dengue fever (DF) and dengue haemorrhagic fever (DHF) analysis using artificial neural network (ANN) |
| title_fullStr | A novel dengue fever (DF) and dengue haemorrhagic fever (DHF) analysis using artificial neural network (ANN) |
| title_full_unstemmed | A novel dengue fever (DF) and dengue haemorrhagic fever (DHF) analysis using artificial neural network (ANN) |
| title_short | A novel dengue fever (DF) and dengue haemorrhagic fever (DHF) analysis using artificial neural network (ANN) |
| title_sort | novel dengue fever df and dengue haemorrhagic fever dhf analysis using artificial neural network ann |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) |
| url | http://eprints.um.edu.my/9322/1/A_novel_dengue_fever_%28DF%29_and_dengue_haemorrhagic_fever_%28DHF%29_analysis_using_artificial_neural_network_%28ANN%29.pdf |
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