Attitudes and Awareness of Medical Students Toward Teleradiology and the Application of Artificial Intelligence in Diagnostic Radiology: A Cross-Sectional Study.

RATIONALE AND OBJECTIVES

Teleradiology and artificial intelligence (AI) have emerged as important tools for facilitating healthcare workers in diagnosing, treating, and preventing diseases. They can also be used in the analysis of X-ray images, magnetic resonance imaging, and computed tomography scans. This study delves into the perceptions of medical students at Imam Abdulrahman University (IAU) regarding the role of AI and teleradiology. The findings also shed light on the opinions of medical students at the IAU regarding the potential augmentation and replacement of radiologists with AI.

MATERIALS AND METHODS

A cross-sectional study was conducted in August 2023 among 292 medical students and interns at Imam Abdulrahman bin Faisal University (IAU), Eastern region, Saudi Arabia, with a response rate of 65.2%. Data were collected using an online self-administered questionnaire. The Chi-square test was applied to evaluate the association between demographic factors and perceptions of AI and teleradiology. Since the study was conducted at a single institution, the findings may not be generalizable to all medical students in Saudi Arabia. Students from other universities with different curricula and exposure to AI/teleradiology may have different perceptions. Future multicenter studies are recommended to provide a broader perspective. Additionally, self-reported data are susceptible to response bias, as participants may provide answers they perceive as socially desirable rather than their true opinions. To minimize this, the questionnaire was anonymous, and students were encouraged to answer honestly. However, the possibility of bias cannot be eliminated.

RESULTS

The study concluded that 65.2% believed that radiologists should embrace AI. Moreover, 56.1% agreed that the AI would augment the radiologist's capability and efficiency. However, 46.2% believed that teleradiology could replace radiologists working at the hospital, and 42.5% agreed that the impact of AI alone would reduce the number of radiologists needed in the field.

CONCLUSION

Medical students expressed different opinions on the role of AI in augmenting or replacing radiologists. As for teleradiology, the results were promising as students showed interest and optimistic views. Understanding and addressing these perceptions from our future physicians is crucial for developing a strong radiology workforce capable of navigating the transformative journey of a more technological healthcare environment.