A novel dual embedding few-shot learning approach for classifying bone loss using orthopantomogram radiographic notes.

Journal: Head & face medicine
Published Date:

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.

Authors

  • Pradeep Kumar Yadalam
    Department of Periodontics, Saveetha Dental College, Saveetha Institute of Medical and Technology Sciences (SIMATS), Saveetha University, Chennai, Tamil Nadu, India.
  • Amit Rajabhau Pawar
    Department of Periodontics, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences (SIMATS), Chennai, 600077, Tamil Nadu, India.
  • Prabhu Manickam Natarajan
    Department of Clinical Sciences, Center of Medical and Bio-allied Health Sciences and Research, College of Dentistry, Ajman University, Ajman, United Arab Emirates.
  • Carlos M Ardila
    Basic Sciences Department, Faculty of Dentistry, Universidad de Antioquia, Medellin, Colombia.