ReviewDiagnostics (Basel, Switzerland)2021
Application and Performance of Artificial Intelligence Technology in Oral Cancer Diagnosis and Prediction of Prognosis: A Systematic Review.
Review in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06862414 (Application and Validation of a Smartphone-based Deep Learning System for Oral Potentially Malignant Disorders), which is not on this map. Cited by 41 papers, 6 of them syntheses that pooled it.
What it found
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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.
Application and Validation of a Smartphone-based Deep Learning System for Oral Potentially Malignant Disorders (OPMD) and Oral Cancer Screening
Who cites it
41 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- MRI-Based Radiomics and Artificial Intelligence for Prediction of Recurrence and Prognostic Outcomes in Oral Tongue Squamous Cell Carcinoma: A Systematic Review with Functional Meta-Synthesis.Medical sciences (Basel, Switzerland) · 2026Pooled it
- Diagnostic performance of artificial intelligence in oral squamous cell carcinoma detection: a higher-order evidence synthesis through umbrella review and meta-meta-analysis.Frontiers in dental medicine · 2026Pooled it
- Diagnosis of Oral Cancer With Deep Learning. A Comparative Test Accuracy Systematic Review.Oral diseases · 2025Pooled it
- Artificial Intelligence Performance in Image-Based Cancer Identification: Umbrella Review of Systematic Reviews.Journal of medical Internet research · 2025Pooled it
- Diagnostic Accuracy of Artificial Intelligence Compared to Biopsy in Detecting Early Oral Squamous Cell Carcinoma: A Systematic Review and Meta Analysis.Asian Pacific journal of cancer prevention : APJCP · 2024Pooled it
- Applications of artificial intelligence in the field of oral and maxillofacial pathology: a systematic review and meta-analysis.BMC oral health · 2024Pooled it
- Artificial Intelligence in Oral and Maxillofacial Surgery-A Narrative Review.Journal of clinical medicine · 2026Review
- A Pilot Study of the Diagnosis of Oral Cancer Through the Development of an AI Application.Dentistry journal · 2026Article
- Article
- 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
- MeMoSA dataset: A multi-country collection of over 30,000 oral mucosa images with clinically labelled lesions.Scientific data · 2026Article
- AI-Supported Digital Microscopy Diagnostics in Primary Health Care Laboratories: Scoping Review.Journal of medical Internet research · 2026Article
- Deep learning-based artificial intelligence models predict survival in patients with oral cavity squamous cell carcinoma.Scientific reports · 2025Article
- AI in Early Diagnosis and Prevention of Oral Cancer: A Systematic Review and Meta-analysis.Journal of pharmacy & bioallied sciences · 2025Review
- Artificial Intelligence in the Diagnosis of Tongue Cancer: A Systematic Review with Meta-Analysis.Biomedicines · 2025Review
- A bibliometric analysis reveals a dynamic growth in the use of artificial intelligence in oral cancer research over three decades.Discover oncology · 2025Article
- Review
- Detection of Architectural Dysplastic Features from Histopathological Imagery of Oral Mucosa Using Neural Networks.Bioengineering (Basel, Switzerland) · 2025Article
- Assessing the Capabilities of Generative Pretrained Transformer-4 in Addressing Open-Ended Inquiries of Oral Cancer.International dental journal · 2025Article
- Artificial Intelligence in Oral Cancer: A Comprehensive Scoping Review of Diagnostic and Prognostic Applications.Diagnostics (Basel, Switzerland) · 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
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Oral cancer (OC) is a deadly disease with a high mortality and complex etiology. Artificial intelligence (AI) is one of the outstanding innovations in technology used in dental science. This paper intends to report on the application and performance of AI in diagnosis and predicting the occurrence of OC. In this study, we carried out data search through an electronic search in several renowned databases, which mainly included PubMed, Google Scholar, Scopus, Embase, Cochrane, Web of Science, and the Saudi Digital Library for articles that were published between January 2000 to March 2021. We included 16 articles that met the eligibility criteria and were critically analyzed using QUADAS-2. AI can precisely analyze an enormous dataset of images (fluorescent, hyperspectral, cytology, CT images, etc.) to diagnose OC. AI can accurately predict the occurrence of OC, as compared to conventional methods, by analyzing predisposing factors like age, gender, tobacco habits, and bio-markers. The precision and accuracy of AI in diagnosis as well as predicting the occurrence are higher than the current, existing clinical strategies, as well as conventional statistics like cox regression analysis and logistic regression.
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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.