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The Role and Applications of Artificial Intelligence in Dental Implant Planning: A Systematic Review

Articolo
Data di Pubblicazione:
2024
Abstract:
Artificial intelligence (AI) is revolutionizing dentistry, offering new opportunities to improve the precision and efficiency of implantology. This literature review aims to evaluate the current evidence on the use of AI in implant planning assessment. The analysis was conducted through PubMed and Scopus search engines, using a combination of relevant keywords, including “artificial intelligence implantology”, “AI implant planning”, “AI dental implant”, and “implantology artificial intelligence”. Selected articles were carefully reviewed to identify studies reporting data on the effectiveness of AI in implant planning. The results of the literature review indicate a growing interest in the application of AI in implant planning, with evidence suggesting an improvement in precision and predictability compared to traditional methods. The summary of the obtained findings by the included studies represents the latest AI developments in implant planning, demonstrating its application for the automated detection of bones, the maxillary sinus, neuronal structure, and teeth. However, some disadvantages were also identified, including the need for high-quality training data and the lack of standardization in protocols. In conclusion, the use of AI in implant planning presents promising prospects for improving clinical outcomes and optimizing patient management. However, further research is needed to fully understand its potential and address the challenges associated with its implementation in clinical practice.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
AI in dental implantology; AI-based implant planning; artificial intelligence in implantology; deep learning in implant dentistry; machine learning in dental implantology; robotics in dental implantology
Elenco autori:
Macri', Monica; D’Albis, Vincenzo; D’Albis, Giuseppe; Forte, Marta; Capodiferro, Saverio; Favia, Gianfranco; Omar Alrashadah, Abdulrahman; Diaz-Flores García, Victor; Festa, Felice
Link alla scheda completa:
https://ricerca.unich.it/handle/11564/841051
Link al Full Text:
https://ricerca.unich.it//retrieve/handle/11564/841051/457262/Artificial%20Intelligence.pdf
Pubblicato in:
BIOENGINEERING
Journal
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URL

https://www.mdpi.com/2306-5354/11/8/778
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