Abstract:

Introduction:
Medical education has always been challenging, and the same is true for neurology education. The complexity of the nervous system and the diversity of neurological disorders make it difficult for students to learn and retain knowledge. To improve the effectiveness of neurology education, there is a need for personalized learning. The use of Artificial Intelligence (AI) in medical education has shown promise in personalized learning. Therefore, the objective of this study is to develop an AI-based platform for personalized learning in neurology education for medical students.

Methods:
We conducted a scoping review to identify the potential of AI in neurology education. The review included articles published in peer-reviewed journals and conference proceedings between 2010 and 2021. We used the following search terms: "neurology education," "personalized learning," "Artificial Intelligence," "machine learning," "deep learning," "natural language processing," and "virtual reality." We screened the titles and abstracts of the identified articles and included those relevant to our study. We extracted information on the AI techniques used, the learning outcomes, and the limitations of the studies.

Results:
The scoping review revealed that AI has the potential to improve neurology education. Various AI techniques, such as machine learning, deep learning, natural language processing, and virtual reality, have been used to personalize learning. AI-based platforms have been shown to improve the understanding and retention of knowledge, reduce the workload of instructors, and provide feedback to students. The limitations of the studies included the lack of a standardized approach to AI-based learning, the need for large datasets, and the need for a robust validation process.

Conclusion:
The use of AI in neurology education has shown promise in personalized learning. The development of an AI-based platform for personalized learning in neurology education for medical students is feasible. The platform should be developed in a way that is interactive, engaging, and effective in improving the understanding and retention of knowledge. The platform should also provide feedback to students and instructors. However, the development of such a platform requires a standardized approach, large datasets, and a robust validation process.

Disclosures:
There is nothing to disclose in regards to the interest of transparency, relationships/activities/interests related to the manuscript. All the data used in this study were obtained from published studies and were analyzed anonymously.

Keywords:

Personalized learning, Artificial Intelligence, deep learning.