Application of AI and Machine Learning in Predicting Dental Diseases - Robina Tasleem, Alayyash Afnan Abdulghaffar Aziz, Fahimullah, Hafiz Mahmood Azam, Doha Rajar, Syed Sarim Ali Shah (Pakistan Journal of Medical & Health Sciences, 2023)
Purpose: This study aims to explore the potential of artificial intelligence (AI) and machine learning (ML) in predicting dental diseases like periodontitis, dental caries, and oral cancer. These are prevalent health issues worldwide, often leading to significant pain and suffering. The study evaluates the predictive capabilities of AI and ML in identifying dental diseases based on variables such as age, smoking and alcohol use, oral hygiene, genetic predisposition, and the frequency of dental check-ups annually. Method: A cross-sectional method and a synthetic dataset are employed in this study. The Statistical Package for the Social Sciences (SPSS) software was used for conducting descriptive statistics, correlations, and logistic regression. Findings: The results demonstrated that the frequency of annual dental check-ups significantly predicts dental disease. However, other variables like age, smoking, alcohol use, oral hygiene, and genetic predisposition did not exhibit a substantial independent connection with dental diseases. Practical Implication: The findings emphasize the importance of regular dental check-ups in mitigating and managing dental diseases. This study provides significant insight for healthcare professionals to encourage patients to maintain routine dental visits for early detection and treatment of oral problems. Conclusion: AI and ML have significant potential to enhance dental healthcare by allowing more accurate and proactive diagnosis and treatment of dental diseases. Nonetheless, future research should consider a broader range of variables and employ advanced AI and ML techniques to develop more comprehensive predictive models for dental disease. Keywords: Artificial Intelligence, Machine Learning, Dental Diseases, Predictive Models, Dental Check-ups, Healthcare, Diagnosis, Treatment.