Amal Adnan Ashour*

Department of Oral and Maxillofacial Surgery and Diagnostic Sciences, Faculty of Dentistry, Taif University, Saudi Arabia

*Corresponding Author: Amal Adnan Ashour, Department of Oral and Maxillofacial Surgery and Diagnostic Sciences, Faculty of Dentistry, Taif University, Saudi Arabia.

Received: April 03, 2024; Published: April 22, 2024

Abstract

The early diagnosis of cancer is pivotal for effective clinical management and Artificial Intelligence (AI) shows promise in enhancing the diagnostic process. This study aimed to advance the understanding of AI's application in the early diagnosis of oral cancer. A comprehensive literature search focused on non-invasive early diagnosis of oral cancer using AI during screening. Previous studies primarily focused on image-based detection methods (including optical imaging, enhancement technology, and cytology) aided by AI models. These studies exhibited heterogeneity, with each employing different algorithms, potentially leading to training data biases and limited comparative data for AI interpretation. While AI shows promise for accurately predicting oral cancer development, several methodological challenges must be addressed alongside AI advancements to enable widespread integration into population-based detection protocols.

Keywords:Oral Cancer; Artificial Intelligence; Screening; Early Diagnosis; Machine Learning; Deep Learning

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Citation

Citation: Amal Adnan Ashour. “Assistance of Artificial Intelligence in the Early Detection of Oral Cancer is Transforming Diagnosis Methods".Acta Scientific Dental Sciences 8.5 (2024): 64-70.

Copyright

Copyright: © 2024 Amal Adnan Ashour. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.