Sign in Subscribe
Artificial intelligence

Artificial Intelligence Enhances Diagnosis of Oral and Maxillofacial Diseases

Strategic Insights

— 1 min read

A new study has investigated the potential of artificial intelligence algorithms in improving the diagnosis and management of oral and maxillofacial diseases. The research, conducted by a team from Qazvin University of Medical Sciences in Iran, highlights the effectiveness of machine learning and deep learning algorithms in detecting and diagnosing various oral and maxillofacial pathologies using advanced imaging techniques such as computerized tomography (CT) and cone-beam computed tomography (CBCT). The study's findings demonstrate the superiority of CBCT over panoramic radiographs in diagnosing dental and odontogenic disorders, with CBCT achieving a higher diagnostic accuracy of 91.4% compared to panoramic images at 84.6%.

Key Takeaways:

  • The study's researchers used a systematic review approach to analyze the current literature on the application of artificial intelligence algorithms in oral and maxillofacial diagnosis.
  • The review considered studies published between 2010 and 2024, focusing on keywords related to radiography, MRI, CT, CBCT, ML, DL, and maxillofacial pathology.
  • The researchers found that deep learning algorithms demonstrated high accuracy and sensitivity in diagnosing dental and odontogenic disorders, often outperforming radiologists.
  • The study highlighted the superior anatomical detail of CBCT, making it a more reliable option for diagnosing oral and dentomaxillofacial disorders.
  • The authors concluded that deep learning algorithms are a valuable tool in precision diagnosis, achieving high accuracy and sensitivity in detecting various pathologies.

Statistics:

  • The accuracy of deep learning algorithms in detecting vertical root fractures was 89.0% for premolars, with a sensitivity of 84.0% and specificity of 94.0%.
  • The GoogLeNet Inception v3 architecture achieved an AUC of 0.914, sensitivity of 96.1%, and specificity of 77.1% for CBCT in detecting dental and odontogenic disorders.
  • CBCT demonstrated a higher diagnostic accuracy of 91.4% compared to panoramic images at 84.6% in diagnosing dental and odontogenic disorders.

Sources:

  • Toward Precision Diagnosis of Maxillofacial Pathologies by Artificial Intelligence Algorithms: A Systematic Review, Journal of Maxillofacial and Oral Surgery, 2025;24(4):1151-1178.
  • NewsRx. Researchers from Qazvin University of Medical Sciences Discuss Findings in Artificial Intelligence (Toward Precision Diagnosis of Maxillofacial Pathologies by Artificial Intelligence Algorithms: A Systematic Review), Health & Medicine Week, August 22, 2025, p 6523.

Read more