Predicting the failure of dental implants using supervised learning techniques

<p>A total of 747 fixtures from patients who completed their prosthodontics treatments.&nbsp;The dependent variable is dental implant failure;&nbsp;a total of 20 independent variables were collected, including age, gender, factors of missing, systemic disease, tobacco smoking, alcohol consumption, betel nut chewing, department of surgeon, surgeon experience, location of implant, bone density, ridge augmentation, Maxillary sinus augmentation, implant system, fixture length, fixture width, types of prosthesis, angle of abutment, and prosthesis fixation.</p>