Harnessing artificial intelligence for predictive modelling in oral oncology: Opportunities, challenges, and clinical Perspectives
Abstract
Artificial intelligence (AI) has emerged as a promising tool in oral oncology, particularly in the field of pre-
diction. This review provides a comprehensive outlook on the role of AI in predicting oral cancer, covering key
aspects such as data collection and preprocessing, machine learning techniques, performance evaluation and
validation, challenges, future prospects, and implications for clinical practice. Various AI algorithms, including
supervised learning, unsupervised learning, and deep learning approaches, have been discussed in the context of
oral cancer prediction. Additionally, challenges such as interpretability, data accessibility, regulatory compli-
ance, and legal implications are addressed along with future research directions and the potential impact of AI on
oral oncology care.