Artificial intelligence-based fuzzy logic systems for predicting radiation protection awareness levels among university population
The present study aims to assess the knowledge level of radiation protection among individuals of Princess Nourah bint Abdulrahman University (PNU) using artificial intelligence baesd fuzzy logic system. This crosssectional study included 428 PNU participants. They were asked to fill in the online q...
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my.sunway.eprints.22682023-06-17T07:48:26Z http://eprints.sunway.edu.my/2268/ Artificial intelligence-based fuzzy logic systems for predicting radiation protection awareness levels among university population Hamd, Zuhal Y. Almohammed, H.I. Lashin, Maha M.A. Yousef, M. Aljuaid, Hanan Khawaji, Sawsan M. Alhussain, Norah I. Salami, Alanoud H. Alsowayan, Rand A. Alshaik, Fatima A. Alshehri, Tahani K. Aldossari, Dalal M. Albogami, Nouf F. Khandaker, Mayeen Uddin * Q Science (General) QA Mathematics TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering The present study aims to assess the knowledge level of radiation protection among individuals of Princess Nourah bint Abdulrahman University (PNU) using artificial intelligence baesd fuzzy logic system. This crosssectional study included 428 PNU participants. They were asked to fill in the online questionnaire, consisting of demographic data, education level, and radiation protection awareness. After informed consent was completed, a statistical package for the social sciences as well as fuzzy logic system was used for data analysis. The participant group consisted of 98.4% females, 96.3% individuals aged 18–28 years (the most common age group), 63.1% bachelor’s degree holders, and 65.7% medical participants. Specialty and radiation protection awareness exhibited significant association (P < 0.05). However, age, education level, and gender did not show a significant association (P > 0.05). PNU individuals in the medical field differed significantly (P > 0.05) with the non-medical individual in their knowledge of radiation protection. This study suggests that PNU individuals in the medical field have a reasonable awareness of radiation protection. However, the general knowledge of nonmedical individuals must be improved to raise awareness. Based on the obtained results by using fuzzy model, this study suggests that the tool can be used in the process of radiation protection awareness in other institutions and areas. Elsevier 2023-07 Article PeerReviewed Hamd, Zuhal Y. and Almohammed, H.I. and Lashin, Maha M.A. and Yousef, M. and Aljuaid, Hanan and Khawaji, Sawsan M. and Alhussain, Norah I. and Salami, Alanoud H. and Alsowayan, Rand A. and Alshaik, Fatima A. and Alshehri, Tahani K. and Aldossari, Dalal M. and Albogami, Nouf F. and Khandaker, Mayeen Uddin * (2023) Artificial intelligence-based fuzzy logic systems for predicting radiation protection awareness levels among university population. Radiation Physics and Chemistry, 28. ISSN 0969-806X https://doi.org/10.1016/j.radphyschem.2023.110888 10.1016/j.radphyschem.2023.110888 |
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Q Science (General) QA Mathematics TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Hamd, Zuhal Y. Almohammed, H.I. Lashin, Maha M.A. Yousef, M. Aljuaid, Hanan Khawaji, Sawsan M. Alhussain, Norah I. Salami, Alanoud H. Alsowayan, Rand A. Alshaik, Fatima A. Alshehri, Tahani K. Aldossari, Dalal M. Albogami, Nouf F. Khandaker, Mayeen Uddin * Artificial intelligence-based fuzzy logic systems for predicting radiation protection awareness levels among university population |
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The present study aims to assess the knowledge level of radiation protection among individuals of Princess Nourah bint Abdulrahman University (PNU) using artificial intelligence baesd fuzzy logic system. This crosssectional study included 428 PNU participants. They were asked to fill in the online questionnaire, consisting of demographic data, education level, and radiation protection awareness. After informed consent was completed, a statistical package for the social sciences as well as fuzzy logic system was used for data analysis. The participant group consisted of 98.4% females, 96.3% individuals aged 18–28 years (the most common age group), 63.1% bachelor’s degree holders, and 65.7% medical participants. Specialty and radiation protection awareness exhibited significant association (P < 0.05). However, age, education level, and gender did not show a significant association (P > 0.05). PNU individuals in the medical field differed significantly (P > 0.05) with the non-medical individual in their knowledge of radiation protection. This study suggests that PNU individuals in the medical field have a reasonable awareness of radiation protection. However, the general knowledge of nonmedical individuals must be improved to raise awareness. Based on the obtained results by using fuzzy model, this study suggests that the tool can be used in the process of radiation protection awareness in other institutions and areas. |
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Article |
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Hamd, Zuhal Y. Almohammed, H.I. Lashin, Maha M.A. Yousef, M. Aljuaid, Hanan Khawaji, Sawsan M. Alhussain, Norah I. Salami, Alanoud H. Alsowayan, Rand A. Alshaik, Fatima A. Alshehri, Tahani K. Aldossari, Dalal M. Albogami, Nouf F. Khandaker, Mayeen Uddin * |
author_facet |
Hamd, Zuhal Y. Almohammed, H.I. Lashin, Maha M.A. Yousef, M. Aljuaid, Hanan Khawaji, Sawsan M. Alhussain, Norah I. Salami, Alanoud H. Alsowayan, Rand A. Alshaik, Fatima A. Alshehri, Tahani K. Aldossari, Dalal M. Albogami, Nouf F. Khandaker, Mayeen Uddin * |
author_sort |
Hamd, Zuhal Y. |
title |
Artificial intelligence-based fuzzy logic systems for predicting radiation protection awareness levels among university population |
title_short |
Artificial intelligence-based fuzzy logic systems for predicting radiation protection awareness levels among university population |
title_full |
Artificial intelligence-based fuzzy logic systems for predicting radiation protection awareness levels among university population |
title_fullStr |
Artificial intelligence-based fuzzy logic systems for predicting radiation protection awareness levels among university population |
title_full_unstemmed |
Artificial intelligence-based fuzzy logic systems for predicting radiation protection awareness levels among university population |
title_sort |
artificial intelligence-based fuzzy logic systems for predicting radiation protection awareness levels among university population |
publisher |
Elsevier |
publishDate |
2023 |
url |
http://eprints.sunway.edu.my/2268/ https://doi.org/10.1016/j.radphyschem.2023.110888 |
_version_ |
1769846268193931264 |
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13.214268 |