Medical students' perceptions of an artificial intelligence (AI) assisted diagnosing program

Area of Science:

• Medical Education
• Artificial Intelligence in Healthcare
• Diagnostic Systems

Background:

• The increasing accessibility of AI-assisted diagnostic systems necessitates evaluating their impact on medical education.
• Understanding first-year medical students' perceptions of AI tools is crucial for future healthcare integration.

Purpose of the Study:

• To assess first-year medical students' perceptions of an AI-assisted diagnostic tool, 'Glass AI.'
• To evaluate student views on AI's role in medical education and future healthcare.

Main Methods:

• First-year medical students used 'Glass AI' for a clinical case during a Cell Physiology pre-clerkship.
• A questionnaire assessed immediate experience, educational potential, and future healthcare implications of AI diagnostic systems.
• Data collected from 73/202 (36.10%) of participating students.

Main Results:

• 96% of students reported increased diagnostic confidence using 'Glass AI.'
• 43% found 'Glass AI' explanations insufficient; 68% raised concerns about AI's impact on the physician workforce.
• Students anticipate a positive future for AI in healthcare, contingent on robust regulations for privacy, safety, liability, bias, and quality of care.

Conclusions:

• First-year medical students recognize the significant role of AI in their academic and professional futures.
• Student acceptance of AI diagnostic tools is linked to the establishment of strict regulatory frameworks addressing ethical and practical concerns.