Topic: Machine Learning and AI in Plastic, Reconstructive, and Cosmetic Surgery

The integration of machine learning (ML) and artificial intelligence (AI) is rapidly transforming the landscape of plastic, reconstructive, and cosmetic surgery. From preoperative planning and intraoperative guidance to postoperative monitoring and outcome prediction, AI-driven technologies offer unprecedented precision, efficiency, and personalization. This Special Issue, “Machine Learning and AI in Plastic, Reconstructive, and Cosmetic Surgery,” aims to provide a comprehensive overview of the latest research, clinical applications, and emerging innovations in this dynamic field.

AI algorithms are increasingly applied to medical imaging, enabling more accurate assessment of anatomical structures, tissue characteristics, and aesthetic outcomes. Predictive modeling and risk stratification tools support surgical decision making and patient counseling, while computer vision and robotic-assisted systems enhance intraoperative accuracy. Furthermore, AI-powered analytics facilitate large-scale data interpretation, identifying patterns that improve procedural planning, complication reduction, and long-term functional and aesthetic results.

This Special Issue will feature original research articles, reviews, and technical reports exploring topics such as AI-driven facial recognition for reconstructive planning, predictive modeling in breast and body contouring procedures, computer-assisted microsurgery, and postoperative outcome analysis using deep learning. By highlighting both the opportunities and challenges of AI adoption, this collection seeks to foster innovation and guide future research, ultimately advancing patient-centered, data-driven care in plastic, reconstructive, and cosmetic surgery.

8 potential article titles aligned with the theme:

1. AI-Powered Preoperative Planning in Reconstructive Surgery: Current Applications and Future Directions;

2. Deep Learning for Predictive Modeling of Postoperative Outcomes in Cosmetic Surgery;

3. Computer Vision and 3D Imaging for Facial Reconstruction: Enhancing Precision with Artificial Intelligence;

4. Machine Learning Algorithms in Microsurgery: Improving Decision-Making and Surgical Accuracy;

5. Automated Risk Assessment and Complication Prediction in Breast and Body Contouring Procedures;

6. AI-Driven Aesthetic Outcome Analysis: Quantifying Results in Cosmetic Surgery;

7. Integrating Robotics and Artificial Intelligence in Reconstructive Procedures: Opportunities and Challenges;

8. Big Data and Machine Learning in Personalized Patient Care: From Image Analysis to Predictive Insights.