Digital dentistry in action: Analysis of clinical outcomes of computer-aided design and manufacturing, three-dimensional printing, and artificial intelligence in tooth defect rehabilitation
 
More details
Hide details
1
DONETSK NATIONAL MEDICAL UNIVERSITY, KROPYVNYTSKYI, UKRAINE
 
2
DANYLO HALYTSKY LVIV NATIONAL MEDICAL UNIVERSITY, LVIV, UKRAINE
 
3
SHUPYK NATIONAL HEALTHCARE UNIVERSITY OF UKRAINE, KYIV, UKRAINE
 
 
Publication date: 2025-11-30
 
 
Wiadomości Lekarskie 2025;(11):2540-2547
 
KEYWORDS
ABSTRACT
Aim: To systematically evaluate the clinical outcomes of digital dentistry technologies - computer-aided design and manufacturing (CAD/CAM), three-dimen sional (3D) printing, and artificial intelligence (AI) - in the rehabilitation of tooth defects, compared to conventional techniques. Materials and Methods: A systematic search of PubMed, Scopus, Web of Science, and the Cochrane Library (up to mid-2025) identified clinical studies on CAD/CAM, 3D-printed dental prostheses, and AI in tooth restoration. Studies reporting survival, complications, patient outcomes, and diagnostic accuracy were included. Thirty-two studies (.1580 patients) met inclusion criteria; 25 were included in quantitative synthesis. The five-year survival of CAD/CAM restorations was ~90%, comparable to conventional crowns. Milled and 3D-printed dentures showed similar satisfaction, with milled types offering better fit and fewer adjustments. Digital workflows shortened production time and reduced costs. AI models detected caries with ~85% sensitivity and ~90% specificity, and AI-based implant planning matched expert accuracy while cutting planning time (.10 min vs 30 min). No safety issues were reported. Conclusions: Digital dentistry (CAD/CAM, 3D printing) achieves high-quality, durable restorations (~90% five-year survival) with greater efficiency and lower cost than conventional methods. AI tools show strong potential for accurate, time-saving diagnostics and treatment planning. Overall, digital methods are safe, effective, and suitable for clinical integration. Further long-term studies, especially on AI-driven workflows and 3D-printed materials, are recommended to confirm sustained outcomes and establish evidence-based standards.
eISSN:2719-342X
ISSN:0043-5147
Journals System - logo
Scroll to top