Document Type : Research Articles
Authors
1
Founder and CEO, Dure Technologies, Geneva, Switzerland.
2
ICMR–National Institute of Health Research (ICMR-NIHR), Jodhpur, Rajasthan, India.
3
Global Health, Jodhpur School of Public Health (JSPH), Jodhpur, Rajasthan, India.
4
Bedford Research Foundation, Bedford, Massachusetts, USA.
5
Public Health, Jodhpur School of Public Health (JSPH), Jodhpur, Rajasthan, India.
Abstract
Background: Oral cancer is a significant health issue in the country, accounting for one-fourth of all cases worldwide. A shortage of specialized healthcare, limited access to screening tools, and diagnostic facilities are key contributors to delayed diagnosis. Artificial Intelligence can be a promising tool for the early screening of oral cancer. However, its application in India remains underexplored and lacks systematic evaluation. Methods: A scoping review was conducted using the Arksey and O’Malley (2005) framework and the approach by Peters et al. (2015). The PRISMA framework was adopted for selecting relevant studies on AI applications for oral cancer screening in India. Studies were systematically searched in PubMed, CINAHL, Scopus, and Google Scholar. Reviewers extracted relevant data and systematically mapped them to identify strengths, weaknesses, opportunities, and threats of AI applications in oral cancer screening within India. Results: Of the 265 identified studies, 33 were selected for final review. Various designs were used, including cross-sectional field evaluations, pilot and prospective studies, scoping and systematic reviews, narrative reviews, and experimental studies. AI methodologies demonstrated high diagnostic accuracy, with strengths in portability, scalability, and affordability in low-resource settings. Weaknesses reported were a lack of standardized data, limited digital literacy, and infrastructural gaps. AI models offer opportunities to enhance screening coverage, integrate multimodal datasets, and support personalized treatment planning. Key threats observed were data variability, lack of regulatory and ethical frameworks, and data privacy concerns. Conclusion: AI offers strengths in improving oral cancer screening in India through early detection and reducing inequities. Despite its promising strengths, AI faces challenges such as scalability, infrastructure gaps, and ethical issues when implemented for oral cancer screening in the Indian context. For the successful integration of AI, technological innovation, robust digital infrastructure, adequate workforce training, and regulatory guidelines are required.
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