9. ARTIFICIAL INTELLIGENCE IN DENTISTRY: FROM DIAGNOSIS TO PERSONALIZED TREATMENT (A LITERATURE REVIEW)

ARTIFICIAL INTELLIGENCE IN DENTISTRY: FROM DIAGNOSIS TO
PERSONALIZED TREATMENT
(A LITERATURE REVIEW)

A.E. Shabykeeva, A.D. Murzaliev
1Asian International University named after Satkynbay Tentishev
Department of Morphological Disciplines
2Kyrgyz State Medical Institute of Retraining and Advanced Training
Inter faculty department of Dentistry

Introduction. Artificial intelligence (AI) is increasingly used in dentistry at all stages — from
diagnosis to personalized treatment. However, a systematic evaluation of its effectiveness across
these stages remains limited.
Methods. A systematic review was conducted in eLibrary, PubMed, and Google Scholar
databases for the period 2019–2024. A total of 47 studies using deep learning algorithms (CNN,
RNN) for radiographic image analysis and treatment planning in orthodontics, implantology,
endodontics, periodontology, and surgical dentistry were included.
AI demonstrates a caries detection accuracy on panoramic radiographs of 94.2%
(sensitivity 92%, specificity 96%), comparable to experienced dentists (92–95%). In
endodontics, root canal length determination accuracy is 91%; in orthodontics, tooth extraction
prediction accuracy is 94%. In periodontology, AI detects bone loss up to 40% earlier than
visual assessment.
Conclusions. Artificial intelligence increases the accuracy of dental diagnostics, reduces the
risk of errors, and optimizes treatment planning. AI serves as a supportive tool, not a
replacement for the clinician. Standardization of algorithms is required for routine clinical
application.
Keywords: artificial intelligence, dentistry, neural networks, computer diagnostics, digital
technologies.