Artificial Intelligence (AI) in Medical Education

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One of the main areas where AI is making a profound effect on medical education is curriculum design.The traditional medical curriculum is mostly based on memorization and therefore it is necessary to follow the transition from the information age to the age of AI (Paranjape, 2019).It's crucial to equip future physicians with information integration skills (Wartman, 2018) from the start of medical training, and to embed this knowledge into medicine.AI-powered analytics enhance curricula by identifying student performance and adapting their curricula to ensure better learning outcomes.For example, AI algorithms can identify areas in which students struggle the most and recommend adjustments to course content or teaching methods which will lead to enhancing the efficiency and effectiveness of medical curricula.Even though the digitalization of the curriculum across all institutions may not be feasible due to financial

Faculty of Medicine, University of Colombo, Sri Lanka
Corresponding author: Prof. I. M. Karunathilake Email: indika@medarc.cmb.ac.lk constraints (Frehywot et al., 2013), many medical schools in Canada and the UK are building curriculum maps (Willett et al., 2008), relying on AI and data for support.
Since the late 1990s, AI-driven approaches have gained traction as important tools in assessing medical students' clinical skills, knowledge retention, and critical thinking abilities.Computer simulations, virtual patients, and automated grading offer more objective feedback (Kononowicz et al., 2019).These developments underscore the transformative potential of AI in medical education, paving the way for more personalized, efficient, and datadriven approaches to student assessment that will ultimately contribute to the preparation of competent and highly skilled healthcare professionals.Nevertheless, it is crucial to continue researching the ethical and pedagogical implications of AI integration in student assessment to ensure its responsible and effective implementation.AI-powered simulated patient encounters provide students with opportunities to practice diagnostic and treatment skills in a risk-free environment.AI-driven virtual reality (VR) and augmented reality (AR) applications develop hands-on training experiences, allowing students to explore the human body and surgical procedures in immersive environments which will allow students to enhance clinical skills acquisition, diagnostic accuracy, and decision-making proficiency.For instance, a study conducted by Densen (2011) highlighted the potential of AI-driven virtual patient simulations in providing realistic and immersive clinical scenarios for students to practice their skills in a safe and controlled environment.According to Rajkomar et al. (2018) (Kulasegaram et al., 2013;Kononowicz et al., 2019).Key ethical concerns revolve around issues of data privacy, the potential for perpetuating bias in algorithms, and the need for transparent decision-making processes (Topol, 2019).The humanistic aspects of medicine, such as empathy and bedside manner, challenge the extent to which AI can fully replace human instructors (Cruess et al., 2016).As AI continues to shape medical education, a thoughtful examination of these ethical dimensions becomes essential to ensure that the benefits are harnessed while mitigating potential risks.
The future of AI in medical education holds exciting possibilities.As AI algorithms become more sophisticated, they can provide real-time feedback during clinical encounters, helping students make better decisions and improve patient care.AI-powered virtual mentors and chatbots can provide continuous support and guidance to learners, making education more accessible and engaging.As the medical field becomes increasingly complex and dynamic, AI technologies are poised to play a pivotal role in tailoring educational experiences to the needs of individual learners (Alexander et al., 2019).Adaptive learning systems can provide personalized content delivery, identifying areas where students require more attention and customizing educational materials accordingly (Ali et al., 2017).Furthermore, virtual and augmented reality simulations can create immersive, high-fidelity clinical scenarios for trainees, enhancing their practical skills and decision-making abilities (Wang et al., 2019).In the Southeast Asian region, AI algorithms are being used to develop adaptive learning systems.These systems assess students' performance, identify areas where they need additional support, and adjust the curriculum accordingly (Lee et al., 2021).Additionally, natural language processing and machine learning can assist in the assessment of students' performance, enabling real-time feedback and continuous improvement (Hammoud et al., 2019).However, it also necessitates careful consideration of ethical concerns, and resource allocation to ensure the responsible and effective utilization of these technologies in preparing future healthcare professionals.
In conclusion, the integration of AI into medical education offers substantial potential for advancing healthcare training.AI technologies can enhance personalized learning experiences, boost practical skills through immersive simulations, and streamline assessment processes.However, careful attention to ethical concerns, including bias, data privacy, and preserving humanistic qualities in medicine, is essential when