Perceptions of Artificial Intelligence in Medicine Among Newly Graduated Interns: A Cross-Sectional Study

Ali H Sanad; Aalaa S Alsaegh; Hasan M Abdulla; Abdulla J Mohamed; Ahmed Alqassab; Sayed Mohamed A Sharaf; Mohamed H Abdulla; Sawsan A Khadem

doi:10.7759/cureus.71216

Perceptions of Artificial Intelligence in Medicine Among Newly Graduated Interns: A Cross-Sectional Study

Cureus. 2024 Oct 10;16(10):e71216. doi: 10.7759/cureus.71216. eCollection 2024 Oct.

Authors

Ali H Sanad¹, Aalaa S Alsaegh¹, Hasan M Abdulla², Abdulla J Mohamed³, Ahmed Alqassab², Sayed Mohamed A Sharaf², Mohamed H Abdulla⁴, Sawsan A Khadem⁵

Affiliations

¹ Faculty of Medicine, Ain Shams University, Cairo, EGY.
² Faculty of Medicine, Mansoura University, Mansoura, EGY.
³ Faculty of Medicine, First Moscow State Medical University, Moscow, RUS.
⁴ School of Medicine, Zhejiang University, Hangzhou, CHN.
⁵ Department of Radiology, Salmaniya Medical Complex, Manama, BHR.

Abstract

Background Artificial intelligence (AI) is rapidly transforming the healthcare sector, enhancing clinical decision-making, improving patient outcomes, and streamlining operations. Despite its promise, the integration of AI raises important questions about ethical considerations, data privacy, and implications for healthcare professionals. Methods This cross-sectional study utilized an online survey to assess the perceptions of newly graduated interns applying to post-graduate programs under the Saudi Commission for Health Specialties. A total of 349 participants were recruited through social media and professional networks. The structured questionnaire included sections on demographic information, awareness of AI, perceived impacts, concerns, training experiences, and future perspectives. Data were analyzed using descriptive and inferential statistics. Results The participants (N=349) were predominantly aged 20-25 years (142, 40.7%) with a higher representation of females (215, 61.6%). Awareness levels varied, with 65 participants (18.6%) reporting not being familiar with AI while 146 participants (41.8%) identified as familiar. A majority perceived AI positively, believing it improves patient diagnosis (114, 32.7%) and reduces medical errors (129, 36.9%). However, significant concerns emerged regarding data privacy (140, 40.1%) and job displacement (110, 31.5%). Notably, 189 participants (54.2%) reported no formal training in AI, highlighting a gap in preparedness. Conclusions The study reveals a mix of optimism and concern among newly graduated interns regarding AI in medicine. There is a critical need for enhanced training and education on AI technologies within medical curricula to prepare future healthcare professionals adequately. Addressing the opportunities and challenges posed by AI can foster a collaborative healthcare environment that prioritizes patient care while maintaining the human element of practice.

Keywords: ai in medicine; artificial intelligence; data privacy; healthcare; job displacement; medical education; medical interns; patient care; perceptions.