A novel dual embedding few-shot learning approach for classifying bone loss using orthopantomogram radiographic notes.
Journal:
Head & face medicine
Published Date:
Jul 11, 2025
Abstract
BACKGROUND: Orthopantomograms (OPGs) are essential diagnostic tools in dental and maxillofacial care, providing a panoramic view of the jaws, teeth, and surrounding bone structures. Detecting bone loss, which indicates periodontal disease and systemic conditions like osteoporosis, is crucial for early diagnosis and treatment planning. Periodontists use OPGs to identify subtle radiographic features that signify different stages of bone loss. Automated systems integrating radiographic imaging with textual notes can enhance diagnostic accuracy and minimize interobserver variability. Radiographic notes, which summarize clinical observations and preliminary interpretations, can be utilized for classification through natural language processing techniques, including Transformer-based models. This study will classify bone loss severity (normal, mild, or severe) from OPG notes using a novel dual-embedding few-shot learning framework.