Oral cancer represents a growing global health concern, with rising incidence and mortality rates particularly in low- and middle-income countries. The disease not only poses significant clinical challenges but also exerts substantial socioeconomic burdens due to treatment costs and productivity losses. This study undertakes a meticulous exploratory data analysis (EDA) to scrutinize epidemiology and socioeconomic repercussions of oral cancers. In this study, the Oral Cancer Prediction Dataset from Kaggle is employed to investigate the relationship between patient demographics, lifestyle habits, and oral cancer diagnosis, providing valuable insights into potential risk factors. The analysis reveals robust correlations between pivotal risk factors, including tobacco consumption, alcohol intake, human papillomavirus (HPV) infection, and betel quid usage, and the diagnosis of oral cancer. Notably, demographic trends manifest a pronounced concentration among males aged 45-65, coupled with a dramatic decline in survival rates during advanced stages, underscoring the severity of the disease. The prevalence of elevated case rates in nations such as India and Pakistan, juxtaposed with the escalating incidence of HPV-related cases in Western countries, elucidates the geographical disparities and the critical influence of regional risk determinants. Furthermore, the substantial economic burden is exemplified by annual productivity losses ranging from 30-180 workdays and treatment expenditures spanning $20,000-$80,000. The importance of early detection is underscored by survival rates approximating 80% in early-stage diagnoses, thereby accentuating the imperative for data-driven methodologies and proactive early detection initiatives in the global campaign against oral cancer. This research elucidates that oral cancer transcends individual health concerns, constituting a complex public health challenge with profound ramifications for societal well-being and economic stability. Consequently, the risk factor mitigation, augmentation of public awareness, and the development of accessible screening programs emerge as critical strategies in the comprehensive management of oral cancer. The findings of this study furnish invaluable insights for policymakers, healthcare practitioners, and researchers, thereby fostering the formulation of more efficacious and evidence-based interventions in the global effort to combat oral cancer.
| Primary Language | English |
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| Subjects | Machine Learning (Other), Artificial Intelligence (Other) |
| Journal Section | Research Article |
| Authors | |
| Submission Date | April 21, 2025 |
| Acceptance Date | July 7, 2025 |
| Publication Date | December 24, 2025 |
| Published in Issue | Year 2025 Volume: 67 Issue: 2 |
Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering licensed under a Creative Commons Attribution 4.0 International License.