ArticleFrontiers in oral health2021
Deep Machine Learning for Oral Cancer: From Precise Diagnosis to Precision Medicine.
Article in Frontiers in oral health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 2 of them syntheses that pooled it.
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Who cites it
20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 85 citations in OpenAlex.
- Artificial Intelligence in Head and Neck Cancer: A Systematic Review of Systematic Reviews.Advances in therapy · 2023Pooled it
- Artificial Intelligence in Head and Neck Cancer: A Systematic Review of Systematic Reviews.Advances in therapy · 2023Pooled it
- Early and late mortality among patients with T1-T3 head and neck squamous cell carcinoma: a machine learning analysis using a SEER population-based cohort study.Scientific reports · 2026Article
- Mapping Artificial Intelligence Research in Oral and Maxillofacial Surgery: A Bibliometric Analysis.International dental journal · 2026Article
- Evaluation of the Detectability of Oral Potentially Malignant Diseases with a Deep Learning Approach: A Retrospective Pilot Study.Journal of imaging informatics in medicine · 2026Article
- An adaptive multiscale local mesh ternary pattern technique with extensive pre-processing and Grey Wolf optimisation based classifiers for oral cancer image classification.Scientific reports · 2026Article
- Explainable vision transformer framework for multi-class classification and prognostic interpretation of oral cancer in histopathology images.Discover oncology · 2026Article
- Harnessing the power of ANN for early detection and prediction of oral cancer.Frontiers in artificial intelligence · 2026Article
- Machine learning for survival outcome in head and neck squamous cell carcinoma: a multicenter validation study.Scientific reports · 2025Observational
- Detect pre-cancerous tongue lesions for early oral cancer diagnosis using deep learning algorithm.Scientific reports · 2025Article
- Differentiation of benign and malignant oral lesions through surface texture analysis and SVM modeling.Clinical oral investigations · 2025Article
- Deep learning-based automated tongue analysis system for assisted Chinese medicine diagnosis.Frontiers in physiology · 2025Article
- Attention-guided convolutional network for bias-mitigated and interpretable oral lesion classification.Scientific reports · 2024Article
- Artificial Intelligence in Head and Neck Cancer: Innovations, Applications, and Future Directions.Current oncology (Toronto, Ont.) · 2024Review
- Automated Analysis of Nuclear Parameters in Oral Exfoliative Cytology Using Machine Learning.Cureus · 2024Article
- Patients with oral tongue squamous cell carcinoma and co‑existing diabetes exhibit lower recurrence rates and improved survival: Implications for treatment.Oncology letters · 2024Article
- Detection of Abnormal Changes on the Dorsal Tongue Surface Using Deep Learning.Medicina (Kaunas, Lithuania) · 2023Article
- Computational Intelligence in Cancer Diagnostics: A Contemporary Review of Smart Phone Apps, Current Problems, and Future Research Potentials.Diagnostics (Basel, Switzerland) · 2023Review
- Article
- EfficientNetSwift: A Lightweight and Precise Deep Learning Model for Detecting Oral Squamous Cell Carcinoma Using Pathological Images.Technology in cancer research & treatmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Oral squamous cell carcinoma (OSCC) is one of the most prevalent cancers worldwide and its incidence is on the rise in many populations. The high incidence rate, late diagnosis, and improper treatment planning still form a significant concern. Diagnosis at an early-stage is important for better prognosis, treatment, and survival. Despite the recent improvement in the understanding of the molecular mechanisms, late diagnosis and approach toward precision medicine for OSCC patients remain a challenge. To enhance precision medicine, deep machine learning technique has been touted to enhance early detection, and consequently to reduce cancer-specific mortality and morbidity. This technique has been reported to have made a significant progress in data extraction and analysis of vital information in medical imaging in recent years. Therefore, it has the potential to assist in the early-stage detection of oral squamous cell carcinoma. Furthermore, automated image analysis can assist pathologists and clinicians to make an informed decision regarding cancer patients. This article discusses the technical knowledge and algorithms of deep learning for OSCC. It examines the application of deep learning technology in cancer detection, image classification, segmentation and synthesis, and treatment planning. Finally, we discuss how this technique can assist in precision medicine and the future perspective of deep learning technology in oral squamous cell carcinoma.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.