School of Medicine Publications
Document Type
Letter to the Editor
Publication Date
2026
Abstract
Oral cancer, particularly oral squamous cell carcinoma, remains a serious health concern, with a poor prognosis and a late diagnosis. Leukoplakia, erythroplakia, lichen planus, and submucous fibrosis are examples of oral potentially malignant disorders that must be detected early but are not always so by traditional, laborious, and subjective diagnostic techniques. In oral cancer, artificial intelligence (AI) and precision medicine are becoming game-changing technologies that enhance individualized care, treatment planning, and diagnostic precision. Complex imaging and histopathology data may be analyzed using machine learning and deep learning algorithms, particularly convolutional neural networks, which can identify patterns that are invisible to the human eye. AI systems based on smartphones have demonstrated expert-level accuracy in identifying oral lesions in recent experiments. Through the discovery of biomarkers and the integration of several omics, AI-driven precision medicine also makes customized treatments possible. Nonetheless, issues with patient privacy, data bias, and the opaque "black box" nature of AI systems persist. The future of proactive, individualized oral cancer care will be shaped by the development of Explainable AI and robust ethical frameworks, both of which are necessary to ensure transparency, trust, and equitable integration.
Recommended Citation
Kumar, N., Kumari, S., Sultana, S., Khan, M. S., Patel, T., & Anand, N. (2026). Early detection in oral cancer: Are we prepared for artificial intelligence-driven precision medicine?. Annals of Medicine and Surgery, 88(1), 1046-1047. https://doi.org/10.1097/MS9.0000000000004397
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.
Publication Title
Annals of Medicine & Surgery
DOI
10.1097/MS9.0000000000004397
Academic Level
faculty
Mentor/PI Department
Medical Education

Comments
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