IDWSDS 2025 - S217: Thriving with Data: Harnessing Machine Learning Techniques to Transform Global

Описание: People have unique experiences in their fight against cancer, these journeys often involve uncertainty. Treatment is most effective when cancer is caught in its earliest stages. However, data can be leveraged to develop models specifically tailored to address this concern. Cancer is a global challenge, underscoring a need to develop statistical techniques and models that can address early detection, screening and treatment. This session explores global data and research on different types of cancer to better understand risk factors, how they vary across ages and gender, how they differ worldwide, and how they have evolved over time. By using machine learning techniques, Country-level cancer data will be analyzed to identify emerging trends, predict future burdens, and highlight regions where survival rates and disease severity are improving despite high environmental and lifestyle risk factors or costly treatment. The session will also use statistical and predictive modeling to simulate key factors influencing cancer diagnosis, treatment, and survival, offering valuable insights for researchers, policymakers, and healthcare providers. By uncovering country-specific cancer risks and effective interventions, this research will show how data-driven strategies can help both individuals and countries adapt and overcome challenges. These strategies will enable them not just to survive, but to thrive in their unique environments.
ORGANIZER and CHAIR and SPEAKER: Christianah Olanrewaju, Brooks Insights, Abuja