Dentists’ Experiences with Unknown Implant Systems and Acceptance of Artificial Intelligence-based Identification Tools

Purpose: Dental implant use has increased substantially in South Korea.However, clinicians often encounter patients with unknown implant systems.Identifying implant systems is essential for maintenance and complication management.Existing methods are fragmented, and empirical data on information-seeking patterns and acceptance of AI-based tools are limited.This study examined dentists' experiences with unidentified implant systems, strategies used to obtain missing information, awareness and use of manual identification services, and willingness to adopt AI-based identification tools. Materials and Methods:A cross-sectional online survey was conducted among licensed dentists in Korea (n = 500).The questionnaire collected information on implant practice patterns, experience with unidentified fixtures, information-seeking methods, awareness and use of manual expertbased identification services, and willingness to use an AI-based identification system.Results: Among the respondents, 96.4% (425/441 respondents who performed implant surgery) reported having encountered cases in which the implant system could not be identified.The most common method for obtaining information was asking patients to contact their previous dentist (53.4%), followed by consulting a colleague (17.4%), contacting the implant company (15.5%),and using a manual identification service (12.7%).Awareness and use of manual identification services were each 36.0%.Most respondents (64.0%) indicated that they could not identify the implant systems on radiographs.Willingness to adopt an AI-based identification tool was high (96.2%),with the largest proportion of "Yes" responses among dentists in their 40s. Conclusion:Unknown implant systems pose challenges in clinical practice.Dentists rely on multiple informal strategies to obtain missing information.Limited awareness of existing services, combined with a strong willingness to adopt AI-based tools, underscores the need for more accessible and efficient implant information support systems.