Perspectives of artificial intelligence in radiology in Jordan: CROSS-SECTIONAL study by radiologists and residents’ sides

Abstract

This study has two aims. The first aim is to investigate the perception of Jordanian radiologists on artificial intelligence (AI) in medical imaging. The second aim is to compare Jordan to similar studies conducted in the USA, EU, and 54 other countries worldwide through a cross-sectional analysis. Drawn from a sample of six public and private institutions in the Hashemite Kingdom of Jordan, information was gathered from 16 radiologists and 14 radiology residents using a 21-question questionnaire delivered via the association's WhatsApp platform and an informal chat. The questionnaire comprised five themes: knowledge of AI, attitude toward AI in radiology, willingness to engage actively, AI integration in radiology training, and Challenges to AI implementation. The findings proved that Jordanian radiologists with over five years of experience and residents with less than five years of experience both apprehend the role of AI, with no statistically significant difference (p-value >0.05). However, compared to radiologists, residents are noticeably more enthusiastic about AI (p-value 0.05). However, they show greater concern about clinical, technical, and regulatory difficulties (p-value <0.01). These findings demonstrate the impression of adopting AI in radiology in Jordan.

Keywords

• Artificial intelligence
• Radiology
• Medical imaging
• Health informatics