Evidence map›Paper›PMID 41158531›Full record

ReviewJournal of oral biology and craniofacial research

Artificial intelligence for maxillofacial prosthodontics: A technological shift in craniofacial rehabilitation- a scoping review.

Anupama Aradya, Koduru Sravani, M B Ravi, K N Raghavendra Swamy, S Ganesh, K Pradeep Chandra, H K Sowmya, B V Jayashankar, Nisarga Vinod Kumar, K M Sangeeta

Abstract readReview
In one paragraph

Review in Journal of oral biology and craniofacial research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Anupama AradyaDept of Prosthodontics and Crown & Bridge JSS Dental College and Hospital, JSS Academy of Higher Education and Research, Mysore, Karnataka, 570015, India.
Koduru SravaniDepartment of Periodontology, Dayanand Sagar College of Dental Sciences, Bengaluru, Karnataka, India.
M B RaviDept of Prosthodontics and Crown & Bridge JSS Dental College and Hospital, JSS Academy of Higher Education and Research, Mysore, India.
K N Raghavendra SwamyDept of Prosthodontics and Crown & Bridge JSS Dental College and Hospital, JSS Academy of Higher Education and Research, Mysore, India.
S GaneshDept of Prosthodontics and Crown & Bridge JSS Dental College and Hospital, JSS Academy of Higher Education and Research, Mysore, India.
K Pradeep ChandraDepartment of Prosthodontics, Dayanand Sagar College of Dental Sciences, Bengaluru, Karnataka, India.
H K SowmyaDepartement of Conservative Dentistry and Endodontics JSS Dental College and Hospital, JSS Academy of Higher Education and Research, Mysore, India.
B V JayashankarDepartment of Prosthodontics and Crown & Bridge, S. Nijalingappa Institute of Dental Sciences and Research, Gulbarga, Karnataka, India.
Nisarga Vinod KumarDept of Prosthodontics and Crown & Bridge JSS Dental College and Hospital, JSS Academy of Higher Education and Research, Mysore, India.
K M SangeetaDept of Pedodontics, Bapuji Dental College and Hospital, Davanagere, Karnataka, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Artificial intelligence (AI) transforms dentistry and holds considerable promise for maxillofacial prosthodontics (MFP). Applications in imaging, computer-aided design and manufacturing (CAD/CAM), and additive manufacturing are improving diagnosis, treatment planning, and prosthetic rehabilitation for patients with craniofacial abnormalities. Despite advances in materials and digital workflows, challenges remain in achieving optimal accuracy, efficiency, and customisation in prosthetic design. The integration of AI in maxillofacial prosthodontics is still in its early stages. Currently, there is no review detailing the scope, trends, potential, and limitations of AI in this field. A scoping review is therefore necessary to consolidate existing evidence, identify knowledge gaps, and suggest directions for future research and clinical application. This review objective is to systematically map and analyse the current literature on AI in maxillofacial prosthodontics, focusing on its role in craniofacial rehabilitation. Methods: This scoping review adhered to the methodological framework of Arksey and O'Malley (2005) and was guided by the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis (2020). Reporting complied with PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) guidelines to ensure clarity and reproducibility. The review was registered with the Open Science Framework (registration number: www.osf.io/3b9jr). Electronic databases, including Medline via PubMed, Scopus, Cochrane Database, Science Direct, Google Scholar, and Semantic Scholar, were searched up to 7 June 2025. Full-text English articles containing the keywords "Artificial Intelligence and Maxillofacial Prosthodontics" and related terms were included. Results: This scoping review included 35 articles from diverse geographic regions. The studies addressed several specific applications of AI in maxillofacial prosthodontics, including the production of implant-supported auricular prostheses, coloration of maxillofacial prostheses, evaluation of facial attractiveness in patients with clefts, capture of 3D impressions of cleft palates, identification of hypernasality, assessment of lip symmetry, and detection of teeth in cleft lip and palate cases Conclusion: Artificial intelligence offers significant opportunities for maxillofacial prosthodontics, especially in imaging, digital design, and prosthesis production. Progress in this area requires interdisciplinary teamwork, large-scale clinical trials, and the development of standardized validation methods to ensure safe and effective clinical application.

Indexed as

Artificial intelligenceCAD/CAMDeep learningDigital dentistryFacial rehabilitationMaxillofacial prosthesis

Identifiers

PMID41158531
PMCPMC12557598

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.