Abstract:

Background:
The advent of AI platforms like ChatGPT-4 and Co-Pilot is transforming medical education, offering unique approaches to knowledge dissemination and application. Understanding their efficacy in clinical teaching and decision-making is crucial for optimizing their educational impact.

Objectives:
This study compares ChatGPT-4 and Co-Pilot in addressing complex clinical scenarios, focusing on accuracy, depth, practicality, and user satisfaction among healthcare educators and professionals.

Methods:
Selected clinical problems – diabetic neuropathy, acute myocardial infarction, and pediatric asthma – were used to query both AI platforms. The responses were assessed for accuracy against current guidelines, depth of explanation, and practical applicability. A blinded survey evaluated user satisfaction among healthcare professionals.

Results:
Preliminary analysis revealed differences in the platforms' response characteristics. ChatGPT-4 provided more detailed, comprehensive explanations, whereas Co-Pilot's responses were concise and direct. User satisfaction varied, with preferences aligning with specific educational and clinical needs.

Conclusion:
The study highlights the importance of choosing the right AI tool in clinical education, based on the specific requirements of the educational context and clinical problem. These findings are instrumental in shaping the integration of AI in medical education, emphasizing the need for customized AI solutions to enhance learning efficacy and clinical decision-making.

Implications:
This research offers valuable insights for medical educators in incorporating AI tools into teaching methodologies. It also provides AI developers with targeted feedback for refining their platforms, ultimately advancing the role of technology in medical education.

Keywords:

AI in Medical Education, ChatGPT-4, Co-Pilot, Clinical Decision-Making, Educational Technology.