Machine learning methods in predicting the risk of malignant transformation of oral potentially malignant disorders: A systematic review.

Journal: International journal of medical informatics
PMID: 38552265

Abstract

BACKGROUND: Oral Potentially Malignant Disorders (OPMDs) refer to a heterogenous group of clinical presentations with heightened rate of malignant transformation. Identification of risk levels in OPMDs is crucial to determine the need for active intervention in high-risk patients and routine follow-up in low-risk ones. Machine learning models has shown tremendous potential in several areas of dentistry that strongly suggest its application to estimate rate of malignant transformation of precancerous lesions.

Authors

  • Simran Uppal
    Faculty of Dentistry, Jamia Millia Islamia, New Delhi, India. Electronic address: simranuppal2142@gmail.com.
  • Priyanshu Kumar Shrivastava
    Faculty of Dentistry, Jamia Millia Islamia, New Delhi, India. Electronic address: priyanshushri25@gmail.com.
  • Atiya Khan
    Faculty of Dentistry, Jamia Millia Islamia, New Delhi, India. Electronic address: atiyakhan4674@gmail.com.
  • Aditi Sharma
    Computer Science Engineering & Information Technology, Institute of Engineering & Technology, Lucknow, Uttar Pradesh, India.
  • Ayush Kumar Shrivastav
    Computer Science and Engineering, Centre for Development of Advanced Computing, Noida, Uttar Pradesh, India. Electronic address: ayush.shrivastav.aks@gmail.com.

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