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2000
Volume 17, Issue 3
  • ISSN: 1876-4029
  • E-ISSN: 1876-4037

Abstract

Background

Artificial Intelligence (AI) combined with nanotechnology could detect oral cancer development in an earlier stage by using various advanced techniques such as biosensors, Raman scattering, bio-imaging, smartphones, and AI applications.

Objective

This study aimed to review the latest developments in sophisticated early oral cancer diagnosis using AI techniques combined with nanotechnologies such as Raman scattering and Oral Squamous Cell Carcinoma (OSCC) imaging models.

Methods

Machine learning includes Gabor filters, Resnet 50 for feature extraction, and nanotechnologies such as Raman scattering. An AI smartphone-based image module helped to detect oral cancers such as high-risk OSCC.

Results

AI systems enhance oral cancer identification. Nano-biosensors and Raman scattering aid in precise detection. AI models, like Convolutional Neural Networks (CNNs), accurately classify oral lesions. Integrating AI, IoT, and smartphones enables remote screening in marginalized communities.

Discussion

Artificial intelligence enhances machine learning (ML) and deep learning (DL) accuracy for oral cancer diagnosis. The hybrid Gabor filter, Resnet 50, and nano-based methods impact treatment.

Conclusion

Artificial intelligence and nano-based oral cancer detection, using ML and DL, offer precise diagnosis. These technological advancements enable early detection and improve treatment outcomes.

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2025-02-10
2025-09-07
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