Title

Artificial intelligence for dental implant classification and peri-implant disease detection: A clinical study

Authors

Gousia Shafat Khan¹, Syed Aaliyah¹, Sunil Pal²*, Rahul Tiwari³, M Smitha⁴, Heena Dixit⁵ & M.C Prashant³ & Thoid Ali³

Affiliation

¹Department of Prosthodontics, Crown & Bridge, Government Dental College and Hospital Srinagar, Srinagar, Jammu and Kashmir, India; ²Department of Prosthodontics, ITS Dental College, Ghaziabad, Uttar Pradesh, India; ³Department of Oral and Maxillofacial Surgery, RKDF Dental College and Research Centre, Sarvepalli Radhakrishnan University, Bhopal, Madhya Pradesh, India; ⁴Department of Prosthodontics, NSVK SV Dental College, Bengaluru, Karnataka, India; ⁵Commisionerate of Health and Family Welfare, Government of Telangana, Hyderabad, India; *Corresponding author

Email

Gousia Shafat Khan - E-mail: gousiashafat@gmail.com
Syed Aaliyah - E-mail: syedaaliyah68@gmail.com Sunil Pal - E-mail: drsunilpal5@gmail.com
Rahul Tiwari - E-mail: rtcfsurgeon@gmail.com
M Smitha - E-mail: dr.smitham@yahoo.co.in
Heena Dixit - E-mail: drheenatiwari@gmail.com
M.C Prashant - E-mail: pillaiprasant@yahoo.com

Article Type

Research Article

Date

Received August 1, 2025; Revised August 31, 2025; Accepted August 31, 2025, Published August 31, 2025

Abstract

Artificial intelligence (AI) is transforming diagnostic accuracy in dental care, particularly in the field of implantology. A prospective research was conducted on 150 patients with 212 previously placed dental implants. The AI system correctly classified 97.2% of implants, with a sensitivity of 96.3% and specificity of 98.0%. For peri-implant disease detection, the system achieved 91.8% sensitivity and 93.4% specificity, with an overall AUC-ROC of 0.94. AI demonstrates high diagnostic performance in both implant classification and peri-implant disease detection.

Keywords

Artificial intelligence, dental implants, peri-implantitis, diagnostic imaging, deep learning

Citation

Khan et al. Bioinformation 21(8): 2361-2364 (2025)

Edited by

Akshaya Ojha

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.