OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 29.03.2026, 19:37

Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.

Impact of artificial intelligence on the future of radiology: A national cross-sectional study among medical students and radiology professionals

2025·1 Zitationen·Journal of Radiation Research and Applied SciencesOpen Access
Volltext beim Verlag öffnen

1

Zitationen

12

Autoren

2025

Jahr

Abstract

The incorporation of artificial intelligence (AI) into radiology has significantly transformed disease detection, treatment planning, and outcome forecasting. Despite its potential to revolutionize the field, the knowledge, attitudes, and practices (KAP) surrounding AI among medical students and radiology professionals in Saudi Arabia are still in the early stages of development. This study aimed to investigate the KAP of medical and radiology professionals in Saudi Arabia regarding the application of AI in radiology. Data were collected through an electronic survey distributed via Google Forms, which reached 1582 participants during the 2024–2025 academic year. The participants included medical and radiology students, radiologists, radiology technicians, and technologists from various regions of the country. The results revealed that 57.8 % of the participants had a basic understanding of AI in radiology, with radiologists exhibiting the highest level of awareness (71.2 %). Females were more likely to recognize the benefits of AI, particularly in automated disease detection (83.5 % vs. 73.9 % in males). Concerns regarding the replacement of radiologists with AI were the most pronounced among radiology students (22.7 %). Participants from the private sector reported higher participation in AI-related courses (60.5 %) and projects (58.7 %) than their public sector counterparts. It has a 79.5 % recognition rate for its role in automated disease detection through imaging tests. Radiologists and radiology students generally expressed positive attitudes toward AI, believing that it could improve diagnostic accuracy and efficiency. However, some participants, particularly radiography students, expressed concerns regarding AI replacing human professionals. This study highlights the importance of refining AI training and fostering a deeper understanding of its potential challenges in radiology. The future of AI in radiology in Saudi Arabia holds great promise, with growing interest despite some concerns.

Ähnliche Arbeiten