Computer-aided dental implant design as part of a medical decision-making support system.

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Authors: A. A. Kijko, А Н Николаенко, М. А. Постников, А. В. Колсанов, I M Bayrikov
Cited by: 1

Abstract

Computer-aided design and production of complex engineering products is an important and well-developed area of information technology implementation. The digital transformation of the healthcare system using modern information technology and artificial intelligence facilitates the adoption of a technocratic approach to the design and production of medical devices, which in turn requires the development of a unified information space for medical engineering, for example, in dentistry, similar to mechanical engineering and instrumentation. Purpose of the study is to develop a new technology for the computer-aided design of dental implants as part of a medical decision-making support system. Materials and methods. Based on the results of a system analysis of current trends and technologies in digital dentistry, a unified architecture for a medical decision support system was proposed, based on the combined use of automated design tools for dental implants, artificial intelligence, and knowledge engineering. Results. A formal logical model of digital dentistry was developed for building a knowledge base and implementing information support. Based on the proposed architecture and formal logic model, software was developed for a system to support medical decision-making for selecting and calculating dental implant parameters. Findings. The proposed technical solutions enable the automation of the design and production of dental implants in accordance with the principles of personalized medicine, thereby reducing the labor intensity of implant selection and parameterization and improving the quality of medical services.

Fields of Study & Subjects

Engineering Technology and Methodologies Ergonomics and Human Factors Healthcare Systems and Public Health

Publication details

Journal / source
Manager Zdravookhranenia
Publisher
Federal Research Institute for Health Organization and Informatics
Pages
129–136
Publication date
21 May 2026