Diagnostic Accuracy of Artificial Intelligence in Bone Density in Implant Surgery: A Systematic Review and Meta-analysis - Zahra Mardani; Ali Salehi; Fatemeh Jabbarpor; Bahare Azizi; Nazanin M-Abdi (International Journal of Scientific Research in Dental and Medical Sciences)
Background and aim: Artificial intelligence has garnered significant attention recently, and its application in medicine and dentistry has been proposed. However, few studies have been done in the field of dental implants. Investigating the factors affecting its accuracy is also very important. Therefore, the present study was conducted to investigate the diagnostic accuracy of artificial intelligence in bone density in implant surgery. Material and methods: The relevant published literature was gathered through a systematic search of four electronic databases: Web of Science, Scopus, MEDLINE/PubMed, and Cochrane. The developed PICO question served as the basis for the search terms. Only articles published in English within the previous five years (January 2019 and February 2025) were included in the search. The accuracy of AI was used as an effect size in a fixed-effects model and inverse-variance methods, with 95% confidence intervals (CI). All data analysis was performed using Stata.v18 software (latest version; year 2025). Results: Artificial intelligence-guided implant surgery was 87% accurate (ES 0.87, 95% CI: -0.01, 1.75). According to meta-regression, a higher bone density increased the risk of angular and implant apex deviations. Conclusions: According to the present meta-analysis, the accuracy of the implant pattern designed with artificial intelligence is high, and bone density is higher than the reasons that can lead to implant deviation.