Harnessing artificial intelligence for predictive modelling in oral oncology: Opportunities, challenges, and clinical Perspectives

• Published in: Oral oncology reports 2024-09, Vol.11, p.100591, Article 100591
• Main Authors: Veeraraghavan, Vishnu Priya, Daniel, Shikhar, Dasari, Arun Kumar, Aileni, Kaladhar Reddy, patil, Chaitra, Patil, Santosh R.
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Clinical practice; Data preprocessing; Deep learning; Machine learning; Oral oncology; Performance evaluation; Prediction
• ISSN: 2772-9060; 2772-9060
• DOI: 10.1016/j.oor.2024.100591

Artificial intelligence (AI) has emerged as a promising tool in oral oncology, particularly in the field of prediction. 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 compliance, and legal implications are addressed along with future research directions and the potential impact of AI on oral oncology care. •AI enhances oral cancer prediction: early detection, personalized treatment, improved outcomes.•Challenges: data quality, interpretability, legal compliance.•Future: interpretable models, collaborative data sharing, regulatory alignment.•Clinical impact: proactive risk assessment, personalized therapy, better patient care.•AI revolutionizes oral oncology: precision medicine, data-driven decision-making.