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Beyond Sequential Teaching: A Concurrent Model for AI in Medicine
Gheorghe Ioan Mihalas1, Daniel Goje1, Andrei Craciun1
1Victor Babes University of Medicine and Pharmacy, Timisoara, Romania.
Studies in Health Technology and Informatics
|May 23, 2026
Summary
A new concurrent teaching model effectively integrates artificial intelligence (AI) theory and practice for medical professionals. This approach enhances understanding and motivation in AI in medicine education.
Area of Science:
- Medical Education
- Artificial Intelligence in Medicine
- Pedagogical Research
Background:
- AI is increasingly vital in medicine, necessitating specialized education for healthcare professionals.
- Traditional AI courses may not adequately bridge theoretical knowledge with clinical application for medical learners.
Purpose of the Study:
- To design and evaluate a concurrent (parallel) teaching model for AI in medicine.
- To integrate theoretical AI concepts with practical clinical applications within a single course structure.
Main Methods:
- A seven-session elective course combining lectures on AI concepts (e.g., machine learning, neural networks) with invited clinical/research application presentations.
- Quantitative analysis of questionnaire data to assess course effectiveness and learner perception.
Main Results:
- The concurrent model demonstrated good internal consistency and was well-received across different professional backgrounds.
- Perceived course impact correlated positively with both theoretical understanding and application-focused content.
Conclusions:
- The concurrent teaching model is appropriate for AI education in medicine.
- Integrating theory and practical applications in each session enhances motivation and understanding for clinically oriented learners.
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