Bulletin of Stomatology and Maxillofacial Surgery
ISSN 1829-006X
2025; 49–51
Shared with The Gufo

AI INTEGRATED WITH LASERS TO DISTINGUISH BETWEEN HEALTHY AND DISEASED TISSUE FOR MINIMALLY INVASIVE PROCEDURES

Praveen Kumar*, Beena George, Prakash Dhanavelu, N. Sayeeganesh, Sruthi V.G, Savita A M

Sree Balaji Dental College and Hospital · Kamineni Institute of Dental Sciences · Vinayaka Missions University · KMCT Group of Educational Institutions · Shavige Malleswara Hills, Kumarswamy layout, Bangalore

Received: 2026-04-08 · Published: 2025-09-21

© 2025 The Author(s) and the original publisher.

CC BY-NC 4.0 This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Shared article.

Originally published in Bulletin of Stomatology and Maxillofacial Surgery, 2025 — https://doi.org/10.58240/1829006X-2025.21.9-49.

Original title
AI INTEGRATED WITH LASERS TO DISTINGUISH BETWEEN HEALTHY AND DISEASED TISSUE FOR MINIMALLY INVASIVE PROCEDURES
Authors
Praveen Kumar, Beena George, Prakash Dhanavelu, N. Sayeeganesh, Sruthi V.G, Savita A M
Source journal
Bulletin of Stomatology and Maxillofacial Surgery
Published
2025-09-21
Licence
Creative Commons Attribution-NonCommercial 4.0 International
Original
https://doi.org/10.58240/1829006X-2025.21.9-49

Abstract

Objective:To evaluate the efficacy of an artificial intelligence (AI)-integrated laser system in distinguishing between healthy and diseased oral soft tissues during minimally invasive surgical procedures. Methods:This prospective in vitro study involved 60 soft tissue biopsy specimens (30 healthy, 30 diseased, including hyperplasia and dysplasia). Near-infrared (NIR) diode laser was paired with a deep learning algorithm trained on spectral and thermal feedback data. The AI model was assessed for sensitivity, specificity, and real-time classification accuracy in differentiating tissues during laser ablation. Results:The AI-laser system assured an overall classification accuracy of 92.1%. Sensitivity and specificity of the diseased tissue detection was 93.3% and 90.8%, respectively. Thermal feedback self-regulation of power output, minimizing collateral damage was (<50 µm peripheral necrosis) compared to standard diode lasers (>100 µm). Conclusion:AI-integrated laser enabled real-time, selective ablation with high precision, reducing tissue trauma surgical complications.
1 / ? 100% Open in new tab Download Cite

Loading the full text…

Download Follow Updates