Knowledge, attitude, and perception of radiologists about artificial intelligence in Nigeria

Abstract

Abstract Introduction: Artificial intelligence (AI) can be described as a set of tools and programs that operate in similar ways to normal human brain functions during regular tasks. Radiology is a medical specialty that is naturally related to technology, and the introduction of AI to radiology offers opportunities to improve the speed, accuracy, and quality of image interpretation. The applications of AI to radiology have gained a lot of grounds in the developed world, but this is still considered alien in some of the low-middle-income countries. Aim: This study aims at evaluating the knowledge level, attitude, and perception of radiologists in Nigeria toward the introduction of AI to the practice of radiology. Materials and Methods: This was a cross-sectional survey carried out on a group of radiologists from all over Nigeria, who were attending an update course in medical imaging. The survey was carried out using a structured interviewee-administered questionnaire to assess knowledge, attitude, and perception of the respondents on the use of AI, machine learning, and deep learning systems in medical imaging. Results: One hundred and sixty-three radiologists participated in the study. It was observed that only 12% had good knowledge of AI. Fifty-eight percent of the respondents were willing to embrace the applications if these were introduced in their hospitals. Sixty percent of the respondents had a positive perception toward the opportunity of using of AI systems in radiology practice within their facilities. There was a strong association between the respondents’ knowledge levels and their respective attitude levels with 82% of those with good knowledge having a positive attitude ( P < 0.001). Conclusion: Knowledge of AI systems in medical imaging is still limited in developing countries like Nigeria, and acceptability of these systems is dependent on the level of knowledge of their applications in medical imaging.

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