Previously submitted to: JMIR Medical Education (no longer under consideration since Mar 21, 2025)
Date Submitted: Sep 28, 2024
Open Peer Review Period: Oct 21, 2024 - Dec 16, 2024
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Advancing AI in Omani Medical Research: Progress, Challenges, and Ethics
ABSTRACT
Background:
Artificial Intelligence (AI) has the potential to transform medical education and research. However, in Omani medical institutions, AI adoption remains limited due to high costs, faculty training needs, and infrastructure challenges. Traditional research methods are less effective in managing the growing complexity of medical data.
Objective:
This innovation sought to improve data analysis and decision-making in Omani medical schools by integrating AI tools such as DataRobot and SAS Viya, aiming to enhance research efficiency and educational outcomes.
Methods:
The study adopted desktop research to map AI Integration gaps in the research process at Sultan Qaboos University (SQU) and other healthcare institutions in Oman. A benchmarking exercise comparing Omani medical schools and healthcare institutions with regional universities like the University of Sharjah College of Medicine and Western institutions such as Harvard Medical School was conducted.
Results:
A gap exists in Integrating AI Tools for data cleaning and preparation and data analysis in research process for medical schools and healthcare institutions in Oman, including SQU. AI tools reduced data processing times by 30% and improved research accuracy.
Conclusions:
AI integration in Omani medical education is both feasible and effective, offering significant improvements in research efficiency and educational outcomes. Continued investment in AI infrastructure and faculty development is critical for maximizing its potential in medical education. Clinical Trial: Not applicable
Citation
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