Artificial intelligence-based fuzzy logic systems for predicting radiation protection awareness levels among university population. (July 2023)

• Record Type: Journal Article
• Authors: Hamd, Zuhal Y.; Almohammed, Huda I.; Lashin, Maha M.A.; Yousef, Mohamed; 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
• Is Part Of: Radiation physics and chemistry. Volume 208(2023)
• Publication Date: 2023-07
• Subjects: Radiation protection -- Awareness prediction -- Artificial intelligence -- Fuzzy logic system -- Ionizing radiation -- PNU; Radiation chemistry -- Periodicals; Radiometry -- Periodicals; Radiation -- Periodicals; Chimie sous rayonnement -- Périodiques; 539.2
• DOI: 10.1016/j.radphyschem.2023.110888
• Languages: English
• ISSNs: 0969-806X

Abstract

Abstract: 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 cross-sectional 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 non-medical 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. Highlights: This study assess radiation protection knowledge among university population. ArTificial intelligence based fuzzy logic system has been employed to analyse the data. Awareness of radiation protection shows significant correlation with specialty of individuals. Fuzzy model provided acceptable results, i.e., it can be used in radiation protection awareness. The knowledge level of non-medical individuals must be improved to raise awareness.