Title
Evaluation of artificial intelligence based prosthetic innovation on dental implants: A database research
Authors
Jay Gohil1,*, Subachander Prabhakaran2, Nishtha Agrawal3, Mithun Ganesh4, Sree Ram Subba Reddy Gudimetla5, Raghavendra Nagappa6 & Rahul Tiwari7
Affiliation
1Department of Prosthodontics, Crown & Bridge, K.M. Shah Dental College & Hospital, Sumandeep Vidyapeeth (Deemed to be University), Waghodia, Vadodara, Gujarat, India; 2Department of Prosthodontics and Crown and Bridge, Meenakshi Ammal Dental College and Hospital, Chennai, Tamil Nadu, India; 3Department of Prosthodontics, Government College of Dentistry, Indore, Madhya Pradesh, India; 4Department of Oral And Maxillofacial Surgery, Sri Sai College of Dental Surgery, Vikarabad, Telangana, India; 5Department of Oral Maxillofacial surgery, Sree Mithra Dental and MaxFace Specialists, Tanuku, Andhra Pradesh, India; 6Department of Periodontics and Oral Implantology, College of Medical Sciences, Bharatpur, Chitwan, Nepal; 7Department of Dental Research Cell, Dr. D. Y. Patil Dental College & Hospital, Dr. D. Y. Patil Vidyapeeth (Deemed to be University), Pimpri, Pune 411018, Maharashtra, India; *Corresponding author
Jay Gohil - E-mail: jagohil92@gmail.com
Subachander Prabhakaran - E-mail: drsubashchanderp@gmail.com
Nishtha Agrawal - E-mail: nishtha.agrawal88@gmail.com
Mithun Ganesh - E-mail: mithunganesh0@gmail.com
Sree Ram Subba Reddy Gudimetla - E-mail: shreeramshree@gmail.com
Raghavendra Nagappa - E-mail: nraghavendradr@yahoo.com
Rahul Tiwari - E-mail: rahul.tiwari@dpu.edu.in
Article Type
Research Article
Date
Received March 1, 2026; Revised March 31, 2026; Accepted March 31, 2026, Published March 31, 2026
Abstract
Accurate radiographic identification of dental implant systems remains challenging in clinical practice when implant documentation is unavailable and manual interpretation of panoramic radiographs is time-consuming and prone to error. Participants and methods deep learning performance was retrospectively evaluated in a database study for automated dental implant system recognition on panoramic radiographs using a labelled institutional image set. Model evaluation was based on accuracy, precision, recall and F1-score on a held-out test set. The top model reached a high diagnostic precision and only low rate of confounding between visually similar implant systems. Thus, we show the potential of using AI-supported implant recognition in prosthetic rehabilitations, especially when no implant documentation is available.
Keywords
Artificial intelligence; deep learning; dental implant; panoramic radiograph; prosthodontics
Citation
Gohil et al. Bioinformation 22(3): 1401-1404 (2026)
Edited by
Vini Mehta
ISSN
0973-2063
Publisher
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.
