article = {DOBCR-2024-1-101}
title = {Role Of Artificial Intelligence in Clinical Diagnosis of Oral Potentially Malignant Disorders: A Scoping Review}
journal = {Dental Oral Biology and Craniofacial Research}
year = {2024}
issn = {2613-4950}
doi = {http://dx.doi.org/10.31487/j.DOBCR.2024.01.01}
url = {https://www.sciencerepository.org/role-of-artificial-intelligence-in-clinical_DOBCR-2024-1-101 
author = {Kriti Agarwal,Krishna Sireesha Sundaragiri,Shikha Saxena,Akshay Bhargava,Bharat Sankhla,Jaswant Singh,}
keywords = {Artificial intelligence, precancerous conditions, neural networks, machine learning, algorithms}
abstract ={Oral potentially malignant disorders encompass a spectrum of lesions that present an increased risk of progressing to oral cancer. Timely and accurate diagnosis, as well as effective risk prediction, are crucial for early intervention and improved patient outcomes. In recent years, the integration of artificial intelligence has emerged as a transformative approach in the realm of medical diagnostics, offering innovative tools to enhance the precision and efficiency of disease identification and risk assessment. Notably, artificial intelligence driven image analysis techniques have demonstrated remarkable potential in interpreting oral lesion images, aiding in the accurate identification of morphological characteristics associated with these oral lesions. This review explores the evolving role of AI in the clinical diagnosis and risk prediction of these disorders.}