Abstract
Artificial intelligence (AI) and machine learning (ML), in the new age of technological progress, provide huge benefits to every area of employment, ranging from IT to health care. To assess the knowledge of, attitude towards, and in-practice use of artificial intelligence and machine learning among radiology residents and faculty radiologists. A web-based questionnaire was distributed via Google Drive to 55 radiologists in the central region of the Kingdom of Saudi Arabia. The questionnaire comprised two sections: three questions regarding demographics and three questions regarding the knowledge, attitudes, and practices (KAP) of AI and ML in radiology. A total of 55 respondents (100%) completed the survey. The majority of respondents claimed familiarity with AI and ML (61.8%). Most radiologists (54.5%) expressed mixed feelings regarding the benefits of AI and ML applications in radiology. Regarding usability, a mixed response was received: 49.1% supported its usability and 45.5% were uncertain of the usability of AI and ML in radiology. Several studies have been conducted which have suggested the usability of AI and ML and their incorporation into the radiology department. The majority of radiologists in Saudi Arabia support the use of AI and ML. Further investigation into the usability of these tools is needed.
Highlights
Artificial intelligence (AI) and machine learning (ML), in the new age of technological progress, provide huge benefits to every area of employment, ranging from IT to health care
Our study findings showed that radiologists practicing in the Kingdom of Saudi Arabia generally have a positive perspective regarding the adoption of AI and ML in radiology facilities
The study findings support existing evidence of the benefits and immense opportunities offered by the AI- and MLrelated tools in the field of radiology, thereby increasing the credibility of the results (Codari et al, 2019)
Summary
Artificial intelligence (AI) and machine learning (ML), in the new age of technological progress, provide huge benefits to every area of employment, ranging from IT to health care. To assess the knowledge of, attitude towards, and in-practice use of artificial intelligence and machine learning among radiology residents and faculty radiologists. The questionnaire comprised two sections: three questions regarding demographics and three questions regarding the knowledge, attitudes, and practices (KAP) of AI and ML in radiology. The majority of radiologists in Saudi Arabia support the use of AI and ML. Recent studies have shown that methods such as convolutional neural networks and variational autoencoders have great potential to advance the field of medical image analysis field in the near future. Rising optimism about radiology’s potential to undergo a hi-tech transformation has led to a steady demand for AI and ML implementation in healthcare practice (Tang et al, 2018). Studies have highlighted key challenges regarding the clinical implementation of ML and AI in the field of radiology and in modern healthcare. The objectives of this research are as follows: 1. Identify knowledge gaps and behavioral patterns that indicate needs regarding, problems with, and barriers to planning and implementing AI and ML
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