OBJECTIVES: The aim of the current study was to evaluate the detection and diagnosis of three types of odontogenic cystic lesions (OCLs)-odontogenic keratocysts, dentigerous cysts, and periapical cysts-using dental panoramic radiography and cone beam...
Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology
38807455
BACKGROUND: The purpose of this systematic review (SR) is to gather evidence on the use of machine learning (ML) models in the diagnosis of intraosseous lesions in gnathic bones and to analyze the reliability, impact, and usefulness of such models. T...
Journal of stomatology, oral and maxillofacial surgery
38719192
This study aimed to assess the diagnostic performance of a machine learning approach that utilized radiomic features extracted from Cone Beam Computer Tomography (CBCT) images and inflammatory biomarkers for distinguishing between Dentigerous Cysts (...
BACKGROUND: The study's objective was to develop an automated method for a histopathology recognition model for odontogenic keratocysts (OKC) and non-keratocyst (Non-KC) in jaw cyst sections stained with hematoxylin (H) and eosin (E) on a tiny bit of...