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Intraoperative Assessment of Resection Margins in Oral Cavity Cancer: This is the Way
Published on: May 10, 2021
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AI-based diagnostic tools for oral cancer: A systematic review
Sindhoori Goud1, Anuj Singh Parihar2, Anuj Mishra3
1Department of Conservative Dentistry and Endodontics, Mallareddy Institute of Dental Science, Mallareddy Viswavidyapet, Hyderabad, Telangana, India.
Bioinformation
|December 30, 2025
Summary
Artificial intelligence (AI) shows promise for early oral cancer detection and diagnosis. While AI models demonstrate high accuracy, challenges in data variability and clinical validation need addressing before widespread use.
Area of Science:
- Oral oncology
- Medical artificial intelligence
- Diagnostic imaging
Background:
- Traditional oral cancer diagnosis methods are subjective and often detect cancer at later stages.
- There is a need for improved, accessible, and objective early detection methods for oral cancer.
Purpose of the Study:
- To evaluate the role of artificial intelligence (AI) in enhancing early detection and diagnosis of oral cancer.
- To review the diagnostic accuracy of AI models, particularly deep learning and convolutional neural networks, in oral oncology.
Main Methods:
- Analysis of recent literature on AI applications in oral cancer diagnosis.
- Focus on deep learning and convolutional neural networks using clinical, histopathological, and optical imaging data.
Main Results:
- AI models, including deep learning and convolutional neural networks, exhibit high diagnostic accuracy across various data types.
- AI demonstrates potential in improving the early detection and diagnosis of oral cancer.
Conclusions:
- Artificial intelligence offers a significant opportunity as a supportive tool in oral oncology.
- Further research is needed on standardized validation and real-world clinical implementation before AI can be widely adopted.
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