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AuthorRokhshad, Rata
AuthorTamimi, Faleh
AuthorBlinvignac, Pauline
AuthorRichert, Raphael
AuthorDucret, Maxime
Available date2025-07-29T10:01:26Z
Publication Date2025-03-27
Publication NameArtificial Intelligence for Oral Health Care Applications and Future Prospects
Identifierhttp://dx.doi.org/10.1007/978-3-031-84047-0_5
CitationRokhshad, R., Tamimi, F., Blinvignac, P., Richert, R., & Ducret, M. (2025). Artificial Intelligence for Prosthetic and Implant Dentistry. In Artificial Intelligence for Oral Health Care: Applications and Future Prospects (pp. 71-79). Cham: Springer Nature Switzerland.‏
ISBN978-3-031-84046-3
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105006955205&origin=inward
URIhttp://hdl.handle.net/10576/66661
AbstractProsthetic and implant dentistry has been at the forefront of adopting digital technologies, integrating cone-beam computed tomography (CBCT) and intraoral scanners for treatment planning, along with computer-aided design and manufacturing (CAD/CAM) for dental prostheses, since their inception. Recently, this field has seen the introduction of artificial intelligence (AI) into a range of solutions and software platforms aimed at digitalizing patients and fabricating dental prostheses. This chapter offers a comprehensive overview of AI solutions in prosthetic and implant dentistry. The body of literature reviewed is primarily composed of pilot studies, case reports, and preclinical research, with a notable scarcity of high-level, empirical studies. Readers are encouraged to critically evaluate these AI solutions, considering them as preliminary steps toward more refined and robust technologies expected to evolve in the near future. The chapter underscores the need for significant advancements to refine and validate these technologies prior to their widespread adoption in daily dental practice.
Languageen
PublisherSpringer Nature Link
SubjectArtificial Intelligence
Dentistry
TitleArtificial Intelligence for Prosthetic and Implant Dentistry
TypeBook chapter
EISBN978-3-031-84047-0
dc.accessType Abstract Only


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