ReviewJournal of maxillofacial and oral surgery2024
Early Detection of Oral Potentially Malignant Disorders: A Review on Prospective Screening Methods with Regard to Global Challenges.
Review in Journal of maxillofacial and oral surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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
10 citing papers in PubMed, 35 citations in OpenAlex.
- Artificial Intelligence in Oncology: A Comprehensive Cross-Cancer Translational Readiness Analysis Across 18 Malignancies.Cancers · 2026Review
- A Report from a Community-Centric Cancer Control Approach in the Post-Conflict Northern Province of Sri Lanka.International journal of environmental research and public health · 2025Article
- Artificial Intelligence and Machine Learning Algorithms-Powered SERS Techniques for Early Theragnosis of Oral Squamous Cell Carcinoma.Journal of maxillofacial and oral surgery · 2025Article
- Artificial Intelligence in Oral Cancer: A Comprehensive Scoping Review of Diagnostic and Prognostic Applications.Diagnostics (Basel, Switzerland) · 2025Review
- Prevalence of oral mucosal lesions among elderly Indian patients: A retrospective study.Bioinformation · 2025Article
- Integrating support vector machines and deep learning features for oral cancer histopathology analysis.Biology methods & protocols · 2025Article
- Role of optical imaging in oral cancer and oral potentially malignant disorders: implications for oral submucous fibrosis.Frontiers in oral health · 2025Review
- The Impact of Oral Microbiome Dysbiosis on the Aetiology, Pathogenesis, and Development of Oral Cancer.Cancers · 2024Review
- Micronuclei detection in oral cytologic smear: does it add diagnostic value?Journal of the Egyptian National Cancer Institute · 2023Article
- AI-Assisted Screening of Oral Potentially Malignant Disorders Using Smartphone-Based Photographic Images.Cancers · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Oral cancer is a cancer type that is widely prevalent in low-and middle-income countries with a high mortality rate, and poor quality of life for patients after treatment. Early treatment of cancer increases patient survival, improves quality of life and results in less morbidity and a better prognosis. To reach this goal, early detection of malignancies using technologies that can be used in remote and low resource areas is desirable. Such technologies should be affordable, accurate, and easy to use and interpret. This review surveys different technologies that have the potentials of implementation in primary health and general dental practice, considering global perspectives and with a focus on the population in India, where oral cancer is highly prevalent. The technologies reviewed include both sample-based methods, such as saliva and blood analysis and brush biopsy, and more direct screening of the oral cavity including fluorescence, Raman techniques, and optical coherence tomography. Digitalisation, followed by automated artificial intelligence based analysis, are key elements in facilitating wide access to these technologies, to non-specialist personnel and in rural areas, increasing quality and objectivity of the analysis while simultaneously reducing the labour and need for highly trained specialists.
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.