Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
The future is already here: how is artificial intelligence changing the way we think about dentistry?
1
Zitationen
4
Autoren
2025
Jahr
Abstract
Background. The article considers artificial intelligence (AI) as a revolutionary technology that is increasingly penetrating various fields of medicine, in particular dentistry, opening up new opportunities for improving the diagnosis, treatment and prevention of oral diseases. The use of AI in modern dentistry is discussed. The purpose is to analyze modern methods for implementing AI in dental practice, to monitor its current impact on diagnosis, treatment and management of clinics, as well as to identify potential prospects for further development, which are already forming a new understanding of future dentistry. Materials and methods. Review and analysis of scientific and medical literature from the Scopus, Web of Science, MEDLINE, PubMed, NCBI databases published in the last 5 years, including literature reviews and research results. Results. The article deals with an overview of the key areas of AI application in dentistry, namely: medical image analysis (radiography, computed tomography); treatment planning (implantology, orthodontics); development of robotics in dentistry; the use of virtual assistants. The article provides a comparative analysis of the advantages and disadvantages of implementing AI in dental practice, which allows assessing the potential opportunities and challenges associated with its use. Conclusions. AI has significant potential to transform the dental industry by improving diagnostic accuracy, optimizing treatment planning, automating routine tasks, and expanding access to medical care. However, the successful implementation of AI requires solving a number of ethical and practical issues, as well as continuous development and adaptation of technologies.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.245 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.100 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.466 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.429 Zit.