Development and Validation of a Machine Learning‐Based Model to Predict Peri‐Implant Mucositis in Patients With Dental Implant Placement After 1‐Year

Key Points

• The aim is to create and validate a machine learning model to predict the occurrence of peri-implant mucositis after one year of dental implant placement.
• Developed a machine learning-based predictive model
• Utilized support vector machine (SVM) for analysis
• Evaluated model performance on risk stratification
• Focused on patients who received dental implants
• Achieved high discriminative ability in predicting mucositis
• Demonstrated clinical utility for risk assessment
• First interpretable tool of its kind in the dental field