Revolutionising Dental Care Through Artificial Intelligence: Applications in Oral Surgery and Diagnostics

Artificial Intelligence, Dental Diagnostics, Oral Surgery, Panoramic Radiography, Deep Learning

Dr. D Shahanaz1
The Apollo University, Assistant Professor,
School of Management, The Apollo University,
Chittoor, 517001, India, Email Id:
d.shahanaz5@gmail.com;
shahanaz_d@apollouniversity.edu.in

Dr. R. SOMASUNDARAM2
SRM Institute of Science & Technology,
Tiruchirapalli, Associate Professor & Program
Coordinator for MBA Healthcare and Hospital
Management, Faculty of Management, SRM
Institute of Science & Technology,
Tiruchirapalli Campus, Tamilnadu,621105,
India, Email Id: somuiau2019@gmail.com;
somasundaram_r@ist.srmtrichy.edu.in
Vinay Joshi3
Founder, InfinAIverse Pvt. Ltd.,
Jaipur, Rajasthan. Email ID:
vinay.joshiii@gmail.com

Dr. N. Sriram Choudary4
Professor, Dhanalakshmi Srinivasan Dental
College, Affiliated to The Tamil Nadu Dr. M.
G. R. Medical University, Email Address:
drsriramchoudary87@gmail.com
Arun Kharavela Mohanty5
Reader, Dept of Prosthodontics, Kalinga
Institute of Dental Sciences, KIIT Deemed to
be University, Bhubaneswar, Odisha, Email ID.
docmohanty89@gmail.com
Dr Shivani Thakre6
Post Graduate student, Department of
Periodontology and Implantology, Sharad
Pawar Dental College, Datta Meghe Institute of
Higher Education and Research, Sawangi,
Wardha, Maharashtra, IndiaEmail Id:
thakareshivani21@gmail.com

European Journal of Prosthodontics and Restorative Dentistry (2026) 34(4s), 448-455

Revolutionising Dental Care
Through Artificial Intelligence:
Applications in Oral Surgery
and Diagnostics

Artificial intelligence (AI) has emerged as a transformative technology in dentistry, offering advanced solutions for diagnostic imaging and oral surgical planning. The present study aimed to evaluate the effectiveness of AI-based deep learning models in dental diagnostics and oral surgery using panoramic radiographic datasets. A retrospective secondary dataset–based research design was employed using the publicly available Dental Disease Panoramic Detection Dataset obtained from Kaggle. Panoramic radiographic images containing dental caries, periodontal bone loss, impacted teeth, periapical lesions, and restorative findings were analyzed using Convolutional Neural Network (CNN)-based architectures, including ResNet50 and VGG16. Prior to model development, image preprocessing and data augmentation techniques were applied to improve dataset quality and model generalizability. The dataset was divided into training, validation, and testing subsets for performance evaluation. The findings demonstrated that the AI models achieved high diagnostic accuracy, sensitivity, and specificity in detecting dental pathologies and surgically relevant anatomical structures. AI-assisted panoramic radiographic interpretation also reduced diagnostic variability and improved clinical efficiency compared with conventional manual interpretation methods. The study highlights the growing potential of AI-driven imaging systems in precision dentistry and oral healthcare. However, further multicenter validation and standardized evaluation frameworks are necessary to support clinical implementation and ensure reliable integration into routine dental practice.

Received-23-05-2026 Revised-25-06-2026 Accepted-29-06-2026

•••••••••••••••••••••••••••••••• ejprd.org - Published by Riset Publication Services LLC

EJPRD

Copyright ©2025 by Riset Publication Services LLC