Artificial Intelligence Innovations in Understanding Oral Submucous Fibrosis: A Nouvelle Modernistic Approach: A Systematic Review

Ankita Bohra ¹, T N Uma Maheswari ², Aditya Harsh ³

⁰17E 748 Chopasni Housing Board, India.

Asian Pacific Journal of Cancer Prevention : Apjcp +

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November 28, 2025

View abstract on PubMed

Summary

Artificial intelligence (AI) and machine learning can aid in the early diagnosis and management of oral submucous fibrosis (OSMF). These technologies offer valuable tools for improving patient care and outcomes in this common precancerous condition.

Area Of Science

Oral Pathology
Medical Informatics
Artificial Intelligence

Background

Oral submucous fibrosis (OSMF) is a prevalent precancerous condition in South Asia.
Early diagnosis of OSMF is crucial to prevent malignant transformation.
Artificial intelligence (AI) offers potential for analyzing patient data and clinical images for diagnosis and treatment planning.

Purpose Of The Study

To evaluate the role of machine learning (ML) software in the diagnosis and management of OSMF.
To assess the utility of AI in assisting oral health professionals with OSMF intervention.
To explore AI's potential in mass population screening and management of OSMF.

Main Methods

A systematic literature search was conducted across major databases (PubMed, Scopus, Web of Science, Cochrane, Google Scholar).
Keywords included "artificial intelligence," "machine learning," "oral submucous fibrosis," "diagnosis," "treatment planning," "image analysis," and "deep neural networks."
Nine relevant studies were selected for review.

Main Results

AI applications show promise in understanding and intervening in OSMF.
Machine learning, particularly deep neural networks, can create effective image prediction models.
AI serves as a valuable diagnostic aid for oral health professionals in managing OSMF.

Conclusions

AI has the potential to significantly improve diagnostic accuracy and patient care in oral pathologies like OSMF.
The application of AI in oral healthcare, especially for OSMF, represents a novel approach for future treatment strategies.
Further development and integration of AI are needed to enhance diagnostic and prognostic outcomes for OSMF patients.

Keywords:

Artificial intelligence Diagnosis Machine Learning Oral submucous fibrosis Predictive modelling