AI may identify dental implant systems accurately on radiography

Health care is entering a new era where data mining is applied to artificial intelligence. The number of dental implant systems has been increasing worldwide. Patient mobility from different dental offices can make identification of implants for clinicians extremely challenging if there are no past available records, and it would be advantageous to use a reliable tool to identify the various implant system designs in the same practice, as there is a great need for identifying the systems in the field of periodontology and restorative dentistry. However, there have not been any studies devoted to using artificial intelligence/convolutional neural networks to classify implant attributes. Thus, the present study used artificial intelligence to identify the attributes of radiographic images of implants. An average accuracy rate of over 95% was achieved with various machine learning networks to identify three implant manufacturers and their subtypes placed during the past 9 years.

This study evaluated the possibility of identifying dental implant systems on radiographs (based on implant attributes) using artificial intelligence (AI)/convolutional neural networks. A 95% accuracy in correctly identifying three implant systems and their subtypes on 657 radiographs was reported. Interface, taper, thread type, apical grooves, and collar were some of the key implant attributes used by the AI program for implant identification.

With numerous dental implant systems available, it sometimes becomes challenging for the clinician to properly identify the implant system, be it for restoration or explantation. In the future, AI-based systems can come in handy and save time for busy clinicians.

Reference:

Chinhua Y. Hsiao, DMD, MS/Hexin Bai, PhD/Haibin Ling, PhD/Jie Yang, DMD, MS

. Artificial Intelligence in Identifying Dental Implant Systems on Radiographs. DOI: 10.11607/prd.5781

Keywords:

AI,identify, dental implant, systems, accurately, radiography, The International Journal of Periodontics & Restorative Dentistry