Artificial Intelligence in Oral Rehabilitation

A special issue of Dentistry Journal (ISSN 2304-6767).

Deadline for manuscript submissions: 31 January 2026 | Viewed by 1169

Special Issue Editors


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Guest Editor Assistant
Department of Interdisciplinary Medicine, University of Bari Al-do Moro, 70124 Bari, Italy
Interests: dental prosthesis; dental materials; periodontology; zirconia; dental implants; oral surgery; minimal invasive dentistry; bone regeneration; digital dentistry

Special Issue Information

Dear Colleagues,

Artificial intelligence (AI) is transforming digital dentistry, bringing unmatched innovation in diagnostics, treatment planning, and execution. By integrating AI-enabled tools in prosthodontics and oral surgery, clinicians are able to achieve higher accuracy, predictability, and efficiency in oral rehabilitation. AI-enabled innovations are transforming the evaluation of occlusion, prosthetic design, and optimization of surgical procedures among dental professionals, with a guarantee of better patient outcomes and optimized workflow.

This Special Issue will cover current applications of AI in oral rehabilitation, encompassing a wide range of topics, including the following:

  • AI in computer-aided occlusal surface modeling and digital prosthodontics.
  • Artificial intelligence-powered occlusion assessment and bite alignment analysis.
  • Automated identification of anatomical structures for precise diagnosis.
  • AI-assisted implant positioning and bone quality assessment.
  • AI-driven optimization of surgical and prosthetic interventions.
  • AI-assisted treatment planning and workflow automation.

By combining cutting-edge research and expert opinions, this Special Issue seeks to provide important insights regarding the revolutionary influence of artificial intelligence on modern dentistry. We invite researchers and healthcare professionals to contribute original research, in-depth reviews, and case studies that focus on the applied applications and future directions of AI in oral rehabilitation.

We look forward to your submissions.

Dr. Saverio Capodiferro
Dr. Massimo Corsalini
Guest Editors

Dr. Giuseppe D'Albis
Guest Editor Assistant

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Keywords

  • oral rehabilitation
  • prosthodontics
  • artificial intelligence
  • implant dentistry
  • dentures
  • digital dentistry

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Published Papers (3 papers)

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Research

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14 pages, 912 KiB  
Article
Evaluation of Large Language Model Performance in Answering Clinical Questions on Periodontal Furcation Defect Management
by Georgios S. Chatzopoulos, Vasiliki P. Koidou, Lazaros Tsalikis and Eleftherios G. Kaklamanos
Dent. J. 2025, 13(6), 271; https://doi.org/10.3390/dj13060271 - 18 Jun 2025
Abstract
Background/Objectives: Large Language Models (LLMs) are artificial intelligence (AI) systems with the capacity to process vast amounts of text and generate human-like language, offering the potential for improved information retrieval in healthcare. This study aimed to assess and compare the evidence-based potential [...] Read more.
Background/Objectives: Large Language Models (LLMs) are artificial intelligence (AI) systems with the capacity to process vast amounts of text and generate human-like language, offering the potential for improved information retrieval in healthcare. This study aimed to assess and compare the evidence-based potential of answers provided by four LLMs to common clinical questions concerning the management and treatment of periodontal furcation defects. Methods: Four LLMs—ChatGPT 4.0, Google Gemini, Google Gemini Advanced, and Microsoft Copilot—were used to answer ten clinical questions related to periodontal furcation defects. The LLM-generated responses were compared against a “gold standard” derived from the European Federation of Periodontology (EFP) S3 guidelines and recent systematic reviews. Two board-certified periodontists independently evaluated the answers for comprehensiveness, scientific accuracy, clarity, and relevance using a predefined rubric and a scoring system of 0–10. Results: The study found variability in LLM performance across the evaluation criteria. Google Gemini Advanced generally achieved the highest average scores, particularly in comprehensiveness and clarity, while Google Gemini and Microsoft Copilot tended to score lower, especially in relevance. However, the Kruskal–Wallis test revealed no statistically significant differences in the overall average scores among the LLMs. Evaluator agreement and intra-evaluator reliability were high. Conclusions: While LLMs demonstrate the potential to answer clinical questions related to furcation defect management, their performance varies. LLMs showed different comprehensiveness, scientific accuracy, clarity, and relevance degrees. Dental professionals should be aware of LLMs’ capabilities and limitations when seeking clinical information. Full article
(This article belongs to the Special Issue Artificial Intelligence in Oral Rehabilitation)
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14 pages, 826 KiB  
Systematic Review
Current Applications of Chatbots Powered by Large Language Models in Oral and Maxillofacial Surgery: A Systematic Review
by Vincenzo Ronsivalle, Simona Santonocito, Umberto Cammarata, Eleonora Lo Muzio and Marco Cicciù
Dent. J. 2025, 13(6), 261; https://doi.org/10.3390/dj13060261 - 11 Jun 2025
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Abstract
Background/Objectives: In recent years, interest has grown in the clinical applications of artificial intelligence (AI)-based chatbots powered by large language models (LLMs) in oral and maxillofacial surgery (OMFS). However, there are conflicting opinions regarding the accuracy and reliability of the information they provide, [...] Read more.
Background/Objectives: In recent years, interest has grown in the clinical applications of artificial intelligence (AI)-based chatbots powered by large language models (LLMs) in oral and maxillofacial surgery (OMFS). However, there are conflicting opinions regarding the accuracy and reliability of the information they provide, raising questions about their potential role as support tools for both clinicians and patients. This systematic review aims to analyze the current literature on the use of conversational agents powered by LLMs in the field of OMFS. Methods: The review was conducted following PRISMA guidelines and the Cochrane Handbook for Systematic Reviews of Interventions. Original studies published between 2023 and 2024 in peer-reviewed English-language journals were included. Sources were identified through major electronic databases, including PubMed, Scopus, Google Scholar, and Web of Science. The risk of bias in the included studies was assessed using the ROBINS-I tool, which evaluates potential bias in study design and conduct. Results: A total of 49 articles were identified, of which 4 met the inclusion criteria. One study showed that ChatGPT provided the most accurate responses compared to Microsoft Copilot (ex-Bing) and Google Gemini (ex-Bard) for questions related to OMFS. Other studies highlighted that ChatGPT-4 can assist surgeons with quick and relevant information, though responses may vary depending on the quality of the questions. Conclusions: Chatbots powered by LLMs can enhance efficiency and decision-making in OMFS routine clinical cases. However, based on the limited number of studies included in this review (four), their performance remains constrained in complex clinical scenarios and in managing emotionally sensitive patient interactions. Further research on clinical validation, prompt formulation, and ethical oversight is essential to safely integrating LLM technologies into OMFS practices. Full article
(This article belongs to the Special Issue Artificial Intelligence in Oral Rehabilitation)
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18 pages, 1968 KiB  
Systematic Review
Immediate Loading of Implants-Supported Fixed Partial Prostheses in Posterior Regions: A Systematic Review
by Giuseppe D’Albis, Marta Forte, Abdulrahman Omar Alrashadah, Lorenzo Marini, Massimo Corsalini, Andrea Pilloni and Saverio Capodiferro
Dent. J. 2025, 13(5), 213; https://doi.org/10.3390/dj13050213 - 15 May 2025
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Abstract
Background: Modern dentistry strives to achieve increasingly less invasive procedures as the ultimate therapeutic goal. The careful selection of suitable candidates for immediate dental implants can offer an opportunity to reduce treatment time, lower the relative costs and improve overall patient satisfaction. [...] Read more.
Background: Modern dentistry strives to achieve increasingly less invasive procedures as the ultimate therapeutic goal. The careful selection of suitable candidates for immediate dental implants can offer an opportunity to reduce treatment time, lower the relative costs and improve overall patient satisfaction. Methods: A systematic search was conducted in March 2025, without any time restrictions, in Medline, Pubmed and Web of Science databases. To identify other related references, further research was performed. Articles related to current knowledge about the immediate loading of dental implants supporting fixed partial prosthesis in the posterior region were included. Articles not available in abstract form and articles not published in the English language were excluded. Results: A total of ten studies were eligible for inclusion in the current study. The search strategy resulted in a survival rate ranging from 86% to 100%, and a failure rate of less than 21.6%, with a mean follow-up of 55.6 months. Statistical analysis revealed no significant differences in survival rates between implants placed in the maxilla and mandible (χ2 = 0.42, p = 0.81, df = 2). Follow-up varied from one to ten years, reflecting variability both in study design and duration. Conclusions: The selected studies highlight the heterogeneity in immediate loading protocols for implant-supported fixed partial prosthesis in the posterior regions, emphasizing the variability in prosthetic materials and implant types, suggesting that immediate loading is a reliable, patient-centered therapeutic option with favorable long-term outcomes. Full article
(This article belongs to the Special Issue Artificial Intelligence in Oral Rehabilitation)
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