Development of neurobehavioral deterioration risk prediction model for welder: a proposed study
Risk prediction model estimate the risk of emerging upcoming outcomes for individual based on several underlying characteristics. In welding process, welders have the high risk to expose with the toxicant element which can harm the neuropsychological of a welder. This proposed study will develop a p...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Penerbit UTHM
2018
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/5960/1/AJ%202018%20%28673%29.pdf |
| _version_ | 1796869285288607744 |
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| author | Paiman, Nuur Azreen Hariri, Azian Masood, Ibrahim Noor, Arma Yusof, Khairul Hazdi Abdullah, Samsuri Idris, Ahmad Fu’ad Mohd Afandi, Mohd Azizi Asmuin, Nor Zelawati Leman, Abdul Mutalib |
| author_facet | Paiman, Nuur Azreen Hariri, Azian Masood, Ibrahim Noor, Arma Yusof, Khairul Hazdi Abdullah, Samsuri Idris, Ahmad Fu’ad Mohd Afandi, Mohd Azizi Asmuin, Nor Zelawati Leman, Abdul Mutalib |
| author_sort | Paiman, Nuur Azreen |
| collection | UTHM |
| description | Risk prediction model estimate the risk of emerging upcoming outcomes for individual based on several underlying characteristics. In welding process, welders have the high risk to expose with the toxicant element which can harm the neuropsychological of a welder. This proposed study will develop a prediction model on neurobehavioral deterioration risk of welders. In order to get the intensity of heavy metal exposure of the welders, airborne personal monitoring and toenail biomarker test will be carried out. Meanwhile, for the neurotoxicity assessment, the workers will undergo the neurobehavioral core test battery and questionnaire survey to identify the neurobehavioral score level. Detail statistical analysis between both assessment results will be carried out for development of prediction model based on artificial neural network. After validation test, the developed artificial neural network prediction model will be applied to another metal base industry for verification purpose. Length of abstract can be proportional to the length of the article. Through this study, it is expected neurobehavioral risk prediction model on detection on early symptoms of neurobehavioral deterioration will be developed This study contribute to better understanding on the effects of heavy metals exposure, especially to central nervous systems among welders. |
| first_indexed | 2024-03-05T21:52:35Z |
| format | Article |
| id | uthm.eprints-5960 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | English |
| last_indexed | 2024-03-05T21:52:35Z |
| publishDate | 2018 |
| publisher | Penerbit UTHM |
| record_format | dspace |
| spelling | uthm.eprints-59602022-01-25T01:39:04Z http://eprints.uthm.edu.my/5960/ Development of neurobehavioral deterioration risk prediction model for welder: a proposed study Paiman, Nuur Azreen Hariri, Azian Masood, Ibrahim Noor, Arma Yusof, Khairul Hazdi Abdullah, Samsuri Idris, Ahmad Fu’ad Mohd Afandi, Mohd Azizi Asmuin, Nor Zelawati Leman, Abdul Mutalib T Technology (General) TK Electrical engineering. Electronics Nuclear engineering Risk prediction model estimate the risk of emerging upcoming outcomes for individual based on several underlying characteristics. In welding process, welders have the high risk to expose with the toxicant element which can harm the neuropsychological of a welder. This proposed study will develop a prediction model on neurobehavioral deterioration risk of welders. In order to get the intensity of heavy metal exposure of the welders, airborne personal monitoring and toenail biomarker test will be carried out. Meanwhile, for the neurotoxicity assessment, the workers will undergo the neurobehavioral core test battery and questionnaire survey to identify the neurobehavioral score level. Detail statistical analysis between both assessment results will be carried out for development of prediction model based on artificial neural network. After validation test, the developed artificial neural network prediction model will be applied to another metal base industry for verification purpose. Length of abstract can be proportional to the length of the article. Through this study, it is expected neurobehavioral risk prediction model on detection on early symptoms of neurobehavioral deterioration will be developed This study contribute to better understanding on the effects of heavy metals exposure, especially to central nervous systems among welders. Penerbit UTHM 2018 Article PeerReviewed text en http://eprints.uthm.edu.my/5960/1/AJ%202018%20%28673%29.pdf Paiman, Nuur Azreen and Hariri, Azian and Masood, Ibrahim and Noor, Arma and Yusof, Khairul Hazdi and Abdullah, Samsuri and Idris, Ahmad Fu’ad and Mohd Afandi, Mohd Azizi and Asmuin, Nor Zelawati and Leman, Abdul Mutalib (2018) Development of neurobehavioral deterioration risk prediction model for welder: a proposed study. International Journal of Integrated Engineering, 10 (5). pp. 122-129. ISSN 2229-838X https://doi.org/10.30880/ijie.2018.10.05.018 |
| spellingShingle | T Technology (General) TK Electrical engineering. Electronics Nuclear engineering Paiman, Nuur Azreen Hariri, Azian Masood, Ibrahim Noor, Arma Yusof, Khairul Hazdi Abdullah, Samsuri Idris, Ahmad Fu’ad Mohd Afandi, Mohd Azizi Asmuin, Nor Zelawati Leman, Abdul Mutalib Development of neurobehavioral deterioration risk prediction model for welder: a proposed study |
| title | Development of neurobehavioral deterioration risk prediction model for welder: a proposed study |
| title_full | Development of neurobehavioral deterioration risk prediction model for welder: a proposed study |
| title_fullStr | Development of neurobehavioral deterioration risk prediction model for welder: a proposed study |
| title_full_unstemmed | Development of neurobehavioral deterioration risk prediction model for welder: a proposed study |
| title_short | Development of neurobehavioral deterioration risk prediction model for welder: a proposed study |
| title_sort | development of neurobehavioral deterioration risk prediction model for welder a proposed study |
| topic | T Technology (General) TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.uthm.edu.my/5960/1/AJ%202018%20%28673%29.pdf |
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