• Artificial intelligence for la...

Treffer: Artificial intelligence for laser-assisted oral surgery: A narrative review of current trends and future perspectives.

Title:
Artificial intelligence for laser-assisted oral surgery: A narrative review of current trends and future perspectives.
Authors:
Sivaramakrishnan G; Bahrain Defence Force Royal Medical Services, Riffa, Bahrain. Electronic address: gowri.sivaramakrishnan@gmail.com., Sridharan K; Department of Pharmacology and Therapeutics, College of Medicine and Health Sciences, Arabian Gulf University, Manama, Bahrain.
Source:
Journal of dentistry [J Dent] 2026 Jan; Vol. 164, pp. 106202. Date of Electronic Publication: 2025 Oct 30.
Publication Type:
Journal Article; Review
Language:
English
Journal Info:
Publisher: Elsevier Country of Publication: England NLM ID: 0354422 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-176X (Electronic) Linking ISSN: 03005712 NLM ISO Abbreviation: J Dent Subsets: MEDLINE
Imprint Name(s):
Publication: Kidlington : Elsevier
Original Publication: Bristol, Eng., Wright.
MeSH Terms:
Artificial Intelligence*/trends , Laser Therapy*/methods , Laser Therapy*/trends , Oral Surgical Procedures*/methods , Oral Surgical Procedures*/trends , Surgery, Computer-Assisted*/trends , Surgery, Computer-Assisted*/methods, Humans ; Neural Networks, Computer ; Machine Learning
Contributed Indexing:
Keywords: Laser surgeries; Laser therapy; Laser tissue ablation; Machine Intelligence; Machine learning; Neural networks; Optical coherence tomography; Oral surgical procedures; Robotic surgical systems; evidence-based dentistry
Entry Date(s):
Date Created: 20251101 Date Completed: 20251208 Latest Revision: 20251208
Update Code:
20251209
DOI:
10.1016/j.jdent.2025.106202
PMID:
41175912
Database:
MEDLINE

Weitere Informationen

Objectives: Artificial intelligence (AI) technologies are increasingly being explored to optimize the precision, safety, and personalization of laser-assisted oral surgical procedures. While lasers offer significant advantages, their efficacy depends on precise calibration to avoid complications. This narrative review synthesizes the current and emerging applications of AI in enhancing both laser-assisted surgical execution and diagnostic imaging, while addressing the associated challenges.
Methodology: A comprehensive review of literature was conducted to evaluate the role of AI technologies, including machine learning, neural networks, and robotics, in laser-assisted oral surgery. Emerging trends such as the AI-driven robotic system and AI-enhanced diagnostic tools (e.g., Optical Coherence Tomography, Raman Spectroscopy) were evaluated. The review also examines challenges like fragmented dental data, high costs, clinical validation needs, ethical concerns, and automation bias.
Results: AI technologies demonstrate significant promise in enhancing precision and efficiency. For example, the CARLO® system achieved osteotomy accuracy within 2 mm deviation in 96% of cases in a multicenter study. Diagnostically, AI algorithms improved sensitivity in detecting oral lesions to over 94%, outperforming traditional clinician-based assessment. However, barriers such as high costs, infrastructure requirements, and the need for robust clinical validation remain. Ethical and regulatory uncertainties further complicate adoption.
Conclusions: AI holds transformative potential in laser-assisted oral surgery, but addressing technical, ethical, and regulatory challenges is crucial. Future research should prioritize large-scale clinical validation, multi-center trials, and comprehensive regulatory frameworks to ensure safe and effective implementation.
Clinical Significance: The integration of AI in laser-assisted oral surgery has the potential to significantly enhance surgical precision, optimize treatment outcomes, and improve overall patient care. Overcoming existing challenges may transform surgical practices, making them more efficient and accessible for clinicians and patients.
(Copyright © 2025 Elsevier Ltd. All rights reserved.)

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.