Predictive 3D Modeling of Orthognathic Surgery Outcomes Using Machine Learning Algorithms: A Systematic Review :.

Area of Science:

• Maxillofacial Surgery
• Artificial Intelligence in Medicine
• 3D Modeling and Simulation

Background:

• Orthognathic surgery corrects maxillofacial deformities for functional and aesthetic purposes.
• Predicting surgical outcomes is crucial for patient care and treatment planning.

Purpose of the Study:

• To systematically review and analyze studies (2020-2025) on machine learning (ML) algorithms in 3D modeling for predicting orthognathic surgery outcomes.
• To assess the current state and trends of AI applications in this field.

Main Methods:

• Systematic review of articles published between 2021-2025 from PubMed and Google Scholar.
• Inclusion criteria: original studies, ML/deep learning for outcome prediction using 3D modeling, English language, full-text access.
• Manual checking of reference lists for comprehensive search.

Main Results:

• 12 studies were included from 42 identified articles.
• ML algorithms (deep neural networks, reinforcement learning, random forest, graph-based models) were used for outcome prediction.
• 3D facial models and CBCT images were commonly used for preoperative design and outcome prediction.

Conclusions:

• Digital technologies, including AI and 3D modeling, are increasingly vital in maxillofacial and cosmetic surgery.
• Virtual planning enhances the precision and predictability of orthognathic procedures.
• These advancements signify a transformation in surgical care for maxillofacial deformities.