Artificial intelligence has been used to identify factors influencing cancer survival rates across 185 countries, according to research published in the journal Annals of Oncology. The AI model analyzed cancer data and health system information to determine which factors, such as access to radiotherapy, universal health coverage, and economic strength, are most closely associated with improved survival rates in each nation.

Researchers from the European Society for Medical Oncology developed the machine learning model to move beyond generalized understandings of cancer survival and pinpoint specific, actionable areas for improvement within individual countries. The study marks the first time AI has been applied on such a global scale to analyze cancer survival determinants.

The AI model works by identifying patterns and correlations within large datasets that might be missed by traditional statistical methods. Machine learning algorithms are trained on existing data to recognize relationships between variables. In this case, the AI was trained on data related to cancer incidence, treatment availability, healthcare infrastructure, and socioeconomic indicators for each country. Once trained, the model can predict how changes in specific factors might impact cancer survival rates.

"This AI provides a powerful new lens for understanding the complex interplay of factors that affect cancer survival," said a lead researcher on the project. "By identifying the most critical areas for improvement in each country, we can help policymakers and healthcare providers make more informed decisions about resource allocation and healthcare strategies."

The findings suggest that while universal health coverage is a significant factor in many countries, the specific interventions needed to improve cancer survival vary widely. For example, in some nations, increasing access to radiotherapy may have the most significant impact, while in others, strengthening primary care services or improving cancer screening programs might be more effective.

The study also highlighted the importance of economic strength, but noted that economic resources alone do not guarantee better cancer survival. The AI model revealed that efficient allocation of resources and effective healthcare policies are crucial for translating economic prosperity into improved health outcomes.

The researchers believe this AI model can be a valuable tool for guiding cancer control efforts worldwide. By providing country-specific insights, it can help tailor interventions to the unique needs and challenges of each nation. The team plans to further refine the model by incorporating additional data sources, such as genetic information and lifestyle factors, to provide an even more comprehensive understanding of cancer survival determinants. The ultimate goal is to create a dynamic, continuously updated resource that can inform cancer control policies and improve outcomes for patients around the world.