BACKGROUND: To develop a new deep learning model for detecting white spot lesions (WSLs), which are commonly observed in patients undergoing orthodontic treatment, and assess its accuracy.
Fenestration and dehiscence (FD) pose significant challenges in dental treatments as they adversely affect oral health. Although cone-beam computed tomography (CBCT) provides precise diagnostics, its extensive time requirements and radiation exposure...
Dental traumatology : official publication of International Association for Dental Traumatology
Jun 9, 2025
AIM: The aim of this study was to evaluate the performance of ChatGPT-4o and Gemini Advanced artificial intelligence-based chatbots (AI-based chatbots) in providing emergency intervention recommendations for dental trauma with intraoral photographs o...
AIM: To evaluate a deep learning (DL) model for detecting keratinized gingiva (KG) in dental photographs and validate its clinical applicability using reference retainers for calibration.
BACKGROUND: While artificial intelligence-driven approaches have shown great promise in dental diagnosis and treatment planning, most research focuses on dental radiographs. Only three studies have explored automated tooth numbering in oral photograp...
American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
Mar 3, 2025
INTRODUCTION: SmileMate (SmileMate, Dental Monitoring SAS, Paris, France) is an artificial intelligence (AI)-based Web site that uses intraoral photographs to assess patients' dental and orthodontic parameters and provide a report. This study aimed t...
BACKGROUND: The aim of our study was to develop and evaluate a deep learning model (BiStageNet) for automatic detection of dens evaginatus (DE) premolars on orthodontic intraoral photographs. Additionally, based on the training results, we developed ...
OBJECTIVES: This study aimed to develop a deep learning (DL) model for the predictive esthetic evaluation of single-implant treatments in the esthetic zone.
OBJECTIVE: The study aims to develop a diagnostic model using intraoral photographs to accurately detect and classify early detection of enamel demineralization on tooth surfaces.
This study evaluates the effectiveness of an Artificial Intelligence (AI)-based smartphone application designed for decay detection on intraoral photographs, comparing its performance to that of junior dentists. Conducted at The Aga Khan University H...
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