Teaching, Learning and Assessing Anatomy with Artificial Intelligence: The Road to a Better Future

Area of Science:

• Medical Education Technology
• Anatomy Instruction
• Artificial Intelligence in Healthcare Education

Background:

• Anatomy is a foundational, yet complex and content-heavy subject in undergraduate medical curricula.
• Traditional anatomy teaching faces challenges with student learning constraints and knowledge retention.
• Existing literature on AI in medicine primarily focuses on diagnostics and treatment, with limited data on its educational applications.

Purpose of the Study:

• To review novel artificial intelligence (AI) techniques for teaching, learning, and assessment in anatomy.
• To explore the advantages and limitations of AI in medical education, particularly in anatomy.
• To discuss lessons learned from AI applications during the COVID-19 pandemic and suggest future directions.

Main Methods:

• Review of recent advancements in AI, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Bayesian U-Net for anatomy education.
• Analysis of AI's benefits such as in-depth learning, data storage, remote teaching, and innovative assessment.
• Discussion of AI's limitations and practical considerations for implementation in medical schools.

Main Results:

• AI techniques show potential for improving the learning and long-term retention of complex anatomical knowledge.
• AI offers innovative assessment methods adaptable to individual learners and can supplement traditional methods.
• The COVID-19 pandemic highlighted the utility of AI in overcoming educational barriers, such as remote learning and resource scarcity (e.g., cadavers).

Conclusions:

• AI presents a significant opportunity to enhance anatomy education, supporting both student professional development and instructor teaching methodologies.
• Future AI applications could include augmented reality experiences for visualizing complex anatomical structures.
• AI can revolutionize anatomy assessment, offering personalized and dynamic evaluation tools for medical students.