Related Experiment Video
Updated: Mar 19, 2026
17:13
Exploring Deep Space - Uncovering the Anatomy of Periventricular Structures to Reveal the Lateral Ventricles of the Human Brain
Published on: October 22, 2017
18.3K
Artificial Intelligence in Anatomic Education: Educational Utility, Safety Boundaries, and Implementation
Kyu-Ho Yi1,2, Jovian Wan3, Isabella Rosellini4,5
1Department of Oral Biology, Division in Anatomy and Developmental Biology, Human Identification Research Institute, Yonsei University College of Dentistry, Seoul, Korea.
The Journal of Craniofacial Surgery
|March 17, 2026
Summary
Artificial intelligence (AI) can enhance medical anatomy education by improving visualization and access to resources. Careful integration with safeguards is crucial to ensure AI complements traditional teaching methods without compromising standards.
Area of Science:
- Medical Education
- Anatomy
- Artificial Intelligence
Background:
- Traditional anatomy teaching faces challenges like limited cadaver availability and high costs.
- Current methods struggle to demonstrate dynamic and patient-specific anatomical relationships effectively.
Purpose of the Study:
- To critically synthesize contemporary artificial intelligence (AI) applications for anatomy education.
- To focus on the educational utility of AI tools, not clinical automation.
- To address validation, risks, bias, and governance of AI in anatomy.
Main Methods:
- Review of AI applications including computer vision, deep learning visualization, learning analytics, and natural language processing.
- Emphasis on educational utility, anatomic accuracy, and potential risks like misinformation and bias.
- Consideration of cost, infrastructure, and professional accountability.
Main Results:
- AI tools show potential to enhance visualization, structured repetition, and access to anatomy educational resources.
- Evidence suggests AI can complement anatomy curricula when implemented with safeguards and human oversight.
- Risks include misinformation, hallucinations, and algorithmic bias, requiring careful validation and governance.
Conclusions:
- AI-supported tools can augment anatomy education, improving trainee preparedness for imaging and procedural planning.
- Careful integration is essential to uphold foundational standards of anatomical training.
- Human oversight and governance are critical for responsible AI implementation in medical education.
