Artificial intelligence-based fuzzy logic systems for predicting radiation protection awareness levels among university population

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

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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.

Item Type: Article
Uncontrolled Keywords: radiation protection; awareness prediction; artificial intelligence; fuzzy logic system; ionizing radiation; PNU
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Others > Non Sunway Academics
Sunway University > School of Engineering and Technology [formerly School of Science and Technology until 2020] > Research Centre for Applied Physics and Radiation Technologies [merged with Centre for Carbon Dioxide Capture and Utilization wef December 2023]
Depositing User: Ms Yong Yee Chan
Related URLs:
Date Deposited: 17 Jun 2023 07:48
Last Modified: 17 Jun 2023 07:48

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