AUTHOR=Karuppan Perumal Manoj Kumar , Rajan Renuka Remya , Kumar Subbiah Suresh , Manickam Natarajan Prabhu 

TITLE=Artificial intelligence-driven clinical decision support systems for early detection and precision therapy in oral cancer: a mini review

JOURNAL=Frontiers in Oral Health

VOLUME=Volume 6 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/oral-health/articles/10.3389/froh.2025.1592428

DOI=10.3389/froh.2025.1592428

ISSN=2673-4842

ABSTRACT=Oral cancer (OC) is a significant global health burden, with life-saving improvements in survival and outcomes being dependent on early diagnosis and precise treatment planning. However, diagnosis and treatment planning are predicated on the synthesis of complicated information derived from clinical assessment, imaging, histopathology and patient histories. Artificial intelligence-based clinical decision support systems (AI-CDSS) provides a viable solution that can be implemented via advanced methodologies for data analysis, and synthesis for better diagnostic and prognostic evaluation. This review presents AI-CDSS as a promising solution through advanced methodologies for comprehensive data analysis. In addition, it examines current implementations of AI-CDSS that facilitate early OC detection, precise staging, and personalized treatment planning by processing multimodal patient information through machine learning, computer vision, and natural language processing. These systems effectively interpret clinical results, identify critical disease patterns (including clinical stage, site, tumor dimensions, histopathologic grading, and molecular profiles), and construct comprehensive patient profiles. This comprehensive AI-CDSS approach allows for early cancer detection, a reduction in diagnostic delays and improved intervention outcomes. Moreover, the AI-CDSS also optimizes treatment plans on the basis of unique patient parameters, tumor stages and risk factors, providing personalized therapy.