PREDICTION OF THE IMMEDIATE LOAD ON IMPLANTS WITH FULL ADENTIA USING DIGITAL SOLUTIONS AND INTELLIGENT ASSISTANTS
Abstract
The authors have implemented a treatment protocol in clinical practice using an intelligent system that predicts the duration of orthopedic loading on implants, taking into account parameters that affect implant osseointegration. This system also utilizes digital technologies that enable all stages of diagnosis, planning, surgical intervention, prosthesis fabrication in a milling center, and its installation in the oral cavity. The aim of the study was to evaluate the survival rate of completely edentulous implants using a temporary structure with immediate loading, taking into account the predicted data of artificial intelligence. The article presents a clinical case of completely edentulous maxilla, which allowed for the patient's rehabilitation using a conditionally removable structure on implants and the restoration of chewing function in the oral cavity. The digital protocol, which was developed by the authors and implemented in clinical practice, was adjusted according to the clinical case. After three and six months, radiographic monitoring of implant survival was performed. The radiographic examination data indicate the absence of bone resorption. The obtained results suggest that this approach significantly accelerates the patient's rehabilitation time. Thus, the period from the initial examination and digital data collection to the installation of a temporary removable appliance takes only five days. Managing patients using a digital protocol for predictive rehabilitation not only reduces the likelihood of dental errors but also shortens the number of treatment stages and duration, while improving the patient's quality of life.
Fields of Study & Subjects
Dental Implant Techniques and Outcomes
Engineering Technology and Methodologies
Reformed Theology and Governance
Publication details
- Journal / source
- Медико-фармацевтический журнал «Пульс»
- Publisher
- Academy of International Scientific Cooperation
- Volume
- 28
- Issue
- 6
- Pages
- 21–21
- Publication date
- 29 May 2026