Abstract:

In modern hospital environments, healthcare professionals face increasingly complex clinical situations that demand training strategies beyond traditional methods. Interns and residents often manage high cognitive workloads while making rapid decisions, making technology-supported educational approaches essential.

This study investigates the role of artificial intelligence (AI) in medical training by analyzing human factors in hospital systems. Conducted at Batna University Hospital, the research combines surveys with interns, residents, and physicians, direct observation of clinical workflows, and analysis of decision-making processes. The aim is to identify key cognitive and organizational challenges affecting learning and to evaluate how AI can enhance training effectiveness.

Findings highlight the potential of AI-based systems to provide adaptive learning pathways, personalized feedback, and decision support tools that improve both educational outcomes and clinical performance. By incorporating human factors principles, these systems help learners manage cognitive load, make better clinical decisions, and acquire skills in a realistic, contextually relevant environment.

This research contributes to the development of innovative medical training strategies, emphasizing the integration of AI and human factors to create smarter, learner-centered educational systems tailored to hospital realities.

Keywords:

Cognitive Ergonomics, Artificial Intelligence, Clinical Reasoning, Decision Support, Medical Education.