Intersection of Artificial Intelligence and Machine Learning in Medical Animation: A Systematic Mapping Study

This systematic mapping study investigates the intersection of Artificial Intelligence (AI) and Machine Learning (ML) with medical animation, an emerging field with transformative potential in healthcare visualization. Using the PRISMA framework, we screened 895 articles from six databases (IEEE Xplore, Scopus, Web of Science, ScienceDirect, PubMed, SpringerLink), selecting 43 peer-reviewed studies published between 2014 and 2024. Our analysis reveals a rising trend in AI/ML-driven medical animations, with key applications in surgical training, patient education, anatomical modeling, and therapeutic interventions. Notably, AI/ML enhances 3D modeling, real-time animation, and virtual reality (VR) integration, as evidenced by studies on craniofacial reconstruction, motion capture, and avatar-based therapy. We identify research gaps, such as limited focus on real-time generative AI applications, and propose future directions for interdisciplinary collaboration. As the first systematic mapping study in this domain, this work provides a comprehensive research landscape and a foundation for advancing AI/ML applications in medical animation.