ReviewBDJ open2025
Artificial intelligence in the study of oral lichen planus characteristics: a review.
Review in BDJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
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
Oral Lichen Planus (OLP) is a common chronic inflammatory disorder with a complex etiology and potential for malignant transformation, posing substantial challenges for clinical diagnosis and management. Conventional diagnostic approaches often depend on clinical experience and subjective assessment, which limits their accuracy and efficiency. Recent advances in artificial intelligence (AI) have introduced novel paradigms for investigating OLP characteristics. This review examines current applications, progress, challenges, and future directions of AI in OLP diagnosis and classification, prediction of disease progression and prognosis, and analysis of molecular features. Through a critical evaluation of existing research, AI demonstrates considerable potential to improve diagnostic objectivity, accelerate clinical decision-making, and reveal underlying disease mechanisms, thereby supporting the development of precision medicine for OLP.
Identifiers
What Socratic 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 Socratic graph.