Accuracy of machine learning in the diagnosis of odontogenic cysts and tumors: a systematic review and meta-analysis.

Journal: Oral radiology
Published Date:

Abstract

BACKGROUND: The recent impact of artificial intelligence in diagnostic services has been enormous. Machine learning tools offer an innovative alternative to diagnose cysts and tumors radiographically that pose certain challenges due to the near similar presentation, anatomical variations, and superimposition. It is crucial that the performance of these models is evaluated for their clinical applicability in diagnosing cysts and tumors.

Authors

  • Priyanshu Kumar Shrivastava
    Faculty of Dentistry, Jamia Millia Islamia, New Delhi, India.
  • Shamimul Hasan
    Department of Oral Medicine and Radiology, Faculty of Dentistry, Jamia Millia Islamia, New Delhi, India.
  • Laraib Abid
    Faculty of Dentistry, Jamia Millia Islamia, New Delhi, India.
  • Ranjit Injety
    Department of Neurology, Christian Medical College & Hospital, Ludhiana, Punjab, India.
  • Ayush Kumar Shrivastav
    Computer Science and Engineering, Centre for Development of Advanced Computing, Noida, Uttar Pradesh, India.
  • Deborah Sybil
    Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Jamia Millia Islamia, New Delhi, India. dsybilg@gmail.com.