Machine Learning Predicts Patient Tangible Outcomes After Dental Implant Surgery

Dental implants have become increasingly important in daily dental offices. The degree of pain and discomfort experienced during a surgical procedure varies from one patient to another. Using advanced machine learning algorithms predict pain, the dentist would make more informed decisions about treatment. This study aims at Predicting postoperative using an AI-based multi-linear regression model. functional parametric association between eight parameters (age, sex, operating technique) patient’s was established following implant surgery. output normalized information regarding both incidence severity immediate post-implant To enhance generalization ability multiple linear (MLR) model avoid overfitting, 825 cases were provided as training set, while 207 given for data authentication. In addition, 45 samples used controls determine model’s prediction accuracy. Evaluation reveals Root Mean Squared Error 0.108477788. prototype predicted AI surgery with 89.6 % Finally, this exhibited clinical viability utility predicting after