ReviewDiagnostics (Basel, Switzerland)2023
A Current Review of Machine Learning and Deep Learning Models in Oral Cancer Diagnosis: Recent Technologies, Open Challenges, and Future Research Directions.
Review in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
38 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Accuracy of artificial intelligence in caries detection: a systematic review and meta-analysis.Head & face medicine · 2025Pooled it
- Automated Detection of Oral Malignant Lesions Using Deep Learning: Scoping Review and Meta-Analysis.Oral diseases · 2025Pooled it
- Quercetin as a Therapeutic Agent for Oral Cancer: Current Evidence and Future Directions.Asia-Pacific journal of clinical oncology · 2026Review
- [Current applications and future perspectives of automation technologies and devices in oral diagnosis and treatment].Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology · 2026Review
- Advancing Tumor Treatment Through Artificial Intelligence and Mathematical Modeling: A Comprehensive Review.Health science reports · 2026Article
- Current Trends in Diagnosis and Early Monitoring of Oral Cavity Cancer: Techniques and Biomarkers.Cancers · 2026Review
- SSDA_AOA: Stacked Sparse Denoising Autoencoder With Archimedes Optimization Algorithm Based Oral Cancer Detection on Histopathological Images.Oral diseases · 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
- Potential screening of oral squamous cell carcinoma using microRNA geno-assay by electrochemical sensing: a new platform in biosensor technology.RSC advances · 2026Article
- A Smartphone-based Comprehensive Dataset of Annotated Oral Cavity Images for Enhanced Oral Disease Diagnosis.Scientific data · 2026Article
- Editorial: Next-generation technologies and multidisciplinary integration for oral cancer diagnosis and treatment.Frontiers in oral health · 2026Article
- Harnessing the power of ANN for early detection and prediction of oral cancer.Frontiers in artificial intelligence · 2026Article
- Artificial intelligence-based miRNA analysis for precision oncology: diagnostic and prognostic insights.Frontiers in molecular biosciences · 2026Review
- Genetic and Epigenetic Biomarkers for the Early Oral Cancerization Risk in Periodontitis Patients.Current issues in molecular biology · 2025Review
- Visualization and bibliometric analysis of global research trends on oral cancer screening and early diagnosis.Discover oncology · 2025Article
- Differentiation of benign and malignant oral lesions through surface texture analysis and SVM modeling.Clinical oral investigations · 2025Article
- Neural network models for diagnosing recurrent aphthous ulcerations from clinical oral images.Scientific reports · 2025Article
- Explainable AI for Oral Cancer Diagnosis: Multiclass Classification of Histopathology Images and Grad-CAM Visualization.Biology · 2025Article
- A hybrid compound scaling hypergraph neural network for robust cervical cancer subtype classification using whole slide cytology images.Scientific reports · 2025Article
- Salivary Biomarkers as a Predictive Factor in Anxiety, Depression, and Stress.Current issues in molecular biology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer is a problematic global health issue with an extremely high fatality rate throughout the world. The application of various machine learning techniques that have appeared in the field of cancer diagnosis in recent years has provided meaningful insights into efficient and precise treatment decision-making. Due to rapid advancements in sequencing technologies, the detection of cancer based on gene expression data has improved over the years. Different types of cancer affect different parts of the body in different ways. Cancer that affects the mouth, lip, and upper throat is known as oral cancer, which is the sixth most prevalent form of cancer worldwide. India, Bangladesh, China, the United States, and Pakistan are the top five countries with the highest rates of oral cavity disease and lip cancer. The major causes of oral cancer are excessive use of tobacco and cigarette smoking. Many people's lives can be saved if oral cancer (OC) can be detected early. Early identification and diagnosis could assist doctors in providing better patient care and effective treatment. OC screening may advance with the implementation of artificial intelligence (AI) techniques. AI can provide assistance to the oncology sector by accurately analyzing a large dataset from several imaging modalities. This review deals with the implementation of AI during the early stages of cancer for the proper detection and treatment of OC. Furthermore, performance evaluations of several DL and ML models have been carried out to show that the DL model can overcome the difficult challenges associated with early cancerous lesions in the mouth. For this review, we have followed the rules recommended for the extension of scoping reviews and meta-analyses (PRISMA-ScR). Examining the reference lists for the chosen articles helped us gather more details on the subject. Additionally, we discussed AI's drawbacks and its potential use in research on oral cancer. There are methods for reducing risk factors, such as reducing the use of tobacco and alcohol, as well as immunization against HPV infection to avoid oral cancer, or to lessen the burden of the disease. Additionally, officious methods for preventing oral diseases include training programs for doctors and patients as well as facilitating early diagnosis via screening high-risk populations for the disease.
Indexed as
Identifiers
What OpenQuestion holds
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.