Artificial Intelligence Applications in Oral and Maxillofacial Surgery-A Narrative Review.
4 affiliations
- 1Department of Oral and Maxillofacial Surgery, School of Dental Medicine, Gray Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel.
- 2Dental Department, Shamir Medical Center, Beer Yaacov 70300, Israel.
- 3School of Dental Medicine, Gray Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel.
- 4Department of Oral Pathology, Oral Medicine and Maxillofacial Imaging, School of Dental Medicine, Gray Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel.
Abstract
Background: The use of artificial intelligence (AI) is rapidly growing in the field of dental medicine and in oral and maxillofacial surgery (OMS). The aim of the present review is to assess current applications of AI in OMS, to evaluate their advantages and limitations, and to identify areas requiring further research. Materials and Methods: A comprehensive search was conducted using PubMed, Scopus, and Google Scholar, with targeted keywords including "artificial intelligence," "deep learning," "machine learning," "oral surgery," "maxillofacial surgery," and "diagnosis "Artificial Intelligence" OR "Machine Learning" OR "Deep Learning" AND "Oral and Maxillofacial Surgery" OR "Oral Surgery" OR "Maxillofacial Surgery" AND "Diagnosis". Of 308 identified studies, 37 met the inclusion criteria focusing on AI-assisted detection interpretation and surgical planning in OMS. Results: AI is effective in identifying anatomical landmarks, evaluating lesions and cysts, diagnosing bone disease like medication-related osteonecrosis of jaws (MRONJ), planning dental implants, and aiding in the classification of fractures and temporomandibular joint (TMJ) disorders. AI can match or outperform human experts in various diagnostic tasks, particularly in panoramic and cone-beam computed tomography (CBCT) image analysis. AI shows promise in early detection of impacted and supernumerary teeth, maxillofacial pathologies, neoplastic conditions, and soft tissue calcifications. Limitations: However, substantial methodological heterogeneity, inconsistent reporting of AI performance metrics, and limited external validation across the included studies constrain direct comparison of results and assessment of the generalizability of reported AI performance. Conclusions: AI may assist clinicians in diagnostic and treatment-related decision-making, but current evidence does not support its use as a replacement for comprehensive clinical assessment and professional judgment.
Related
- Generative Artificial Intelligence in Health Research and Care: A Narrative Review of Applications and Implications for Alzheimer’s Disease and Related Dementia
- Artificial Intelligence Applications in Laser-Assisted Refractive Surgery—A Comprehensive Review
- Artificial Intelligence and Anatomical Variation: A Narrative Review of Detection, Classification, and Educational Applications.
- Artificial intelligence in orthodontics: clinical maturity, evidence gaps, and emerging applications-a narrative review.
- Advances in Multimodal Artificial Intelligence in Radiology: Data Integration, Foundation Models, and Clinical Applications-A Narrative Review.
BibTeX
@article{manor2026artificial,
title = {{Artificial Intelligence Applications in Oral and Maxillofacial Surgery-A Narrative Review.}},
author = {Yifat Manor and Lir Abergil and Shoshana Reiter and Gil Ben-Izhack},
journal = {Dentistry journal},
year = {2026},
month = oct,
doi = {10.3390/dj14100668},
url = {https://europepmc.org/article/MED/42930434},
note = {CC BY},
}
RIS
TY - JOUR
TI - Artificial Intelligence Applications in Oral and Maxillofacial Surgery-A Narrative Review.
AU - Yifat Manor
AU - Lir Abergil
AU - Shoshana Reiter
AU - Gil Ben-Izhack
PY - 2026
DA - 2026/10/13
JO - Dentistry journal
DO - 10.3390/dj14100668
UR - https://europepmc.org/article/MED/42930434
AB - Background: The use of artificial intelligence (AI) is rapidly growing in the field of dental medicine and in oral and maxillofacial surgery (OMS). The aim of the present review is to assess current applications of AI in OMS, to evaluate their advantages and limitations, and to identify areas requiring further research. Materials and Methods: A comprehensive search was conducted using PubMed, Scopus, and Google Scholar, with targeted keywords including "artificial intelligence," "deep learning," "machine learning," "oral surgery," "maxillofacial surgery," and "diagnosis "Artificial Intelligence" OR "Machine Learning" OR "Deep Learning" AND "Oral and Maxillofacial Surgery" OR "Oral Surgery" OR "Maxillofacial Surgery" AND "Diagnosis". Of 308 identified studies, 37 met the inclusion criteria focusing on AI-assisted detection interpretation and surgical planning in OMS. Results: AI is effective in identifying anatomical landmarks, evaluating lesions and cysts, diagnosing bone disease like medication-related osteonecrosis of jaws (MRONJ), planning dental implants, and aiding in the classification of fractures and temporomandibular joint (TMJ) disorders. AI can match or outperform human experts in various diagnostic tasks, particularly in panoramic and cone-beam computed tomography (CBCT) image analysis. AI shows promise in early detection of impacted and supernumerary teeth, maxillofacial pathologies, neoplastic conditions, and soft tissue calcifications. Limitations: However, substantial methodological heterogeneity, inconsistent reporting of AI performance metrics, and limited external validation across the included studies constrain direct comparison of results and assessment of the generalizability of reported AI performance. Conclusions: AI may assist clinicians in diagnostic and treatment-related decision-making, but current evidence does not support its use as a replacement for comprehensive clinical assessment and professional judgment.
SN - 2304-6767
ER -