Exploring the Knowledge, Attitudes, and Practices of Radiographers Regarding the Use of Artificial Intelligence in CT in Selected Private Hospitals in KZN

Abstract

Artificial Intelligence (AI) has become increasingly important to daily lives. AI has introduced several algorithms in Computed Tomography (CT) which allow for improved image quality at a low dose. These systems execute tasks that are normally done by a human (Radiographers). Hence Radiographers need to have adequate knowledge of these AI applications. Previous studies reveal that Radiographers lack knowledge of the AI and its algorithms that are used in CT, which has been identified as a problem because limited information is passed on to students and trainees. The aim of this study was to explore Radiographers’ knowledge, attitudes, and practices toward the use of AI in CT. The research was conducted in selected private hospitals in Kwa-Zulu Natal in which semi-structured and in-depth face to face interviews using open-ended questions were used to collect data from 10 participants. Three main themes generated from the study’s theoretical framework were used for data analysis, namely knowledge, attitudes, and practices. Findings in this study indicate that Radiographers lack knowledge of AI and its algorithms that are used in CT. Their lack of knowledge is a result of a lack of training and education. Findings also suggest that a lack of knowledge contributes to uncertainty about the potential impact of AI implementation. However, Radiographers demonstrated interest in wanting to gain more information. Radiographers that participated in this study demonstrated a lack of knowledge, but also an interest in learning more about AI. This, therefore, necessitates collaboration between educational institutes and professional organizations to develop structured training programs for Radiographers.

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