Advancing AI in Omani Medical Research: Progress, Challenges, and Ethics

Abstract

Objective: Artificial Intelligence (AI) holds significant potential to transform medical education and research. However, its adoption in Omani medical institutions remains limited due to high costs, inadequate faculty training, and infrastructural constraints. Traditional research approaches are increasingly insufficient to manage the complexity and scale of modern medical data. This study explores the integration of AI tools—such as DataRobot and SAS Viya—within Omani medical schools to enhance data analysis, research efficiency, and educational outcomes. Methods: Desktop research was conducted to assess AI integration gaps at Sultan Qaboos University (SQU) and other medical institutions in Oman. A benchmarking comparison was performed with regional (University of Sharjah College of Medicine) and global (Harvard Medical School) institutions. Results: Significant gaps were identified in AI adoption, particularly in data cleaning, preparation, and analysis. Institutions using AI tools reported a 30% reduction in data processing time and improved research accuracy. Conclusion: AI integration in Omani medical education is both feasible and beneficial. For sustainable implementation, continued investment in infrastructure, faculty development, and regional collaboration is essential.

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