AI Insight
An international study presented at the ESMO Congress 2026 demonstrates that machine learning models can analyze routinely collected health data—including blood test results, medical histories, and lifestyle information—to identify individuals at elevated risk for several common types of cancer. The approach leverages existing healthcare data rather than requiring specialized screening tests. This method could enable earlier risk stratification across multiple cancer types using information already available in standard medical records.
Why it matters
This technology could enable healthcare systems to implement proactive, personalized cancer screening programs without additional invasive testing or significant costs. By identifying high-risk individuals earlier using existing data, medical resources could be targeted more efficiently, potentially improving early detection rates and outcomes for common cancers.
Understand the Science
Machine learning models using routinely collected health information, such as blood tests, medical history and lifestyle factors, could help identify people at higher risk of several common cancers, according to an international study reported at the ESMO Congress 2026.
Source: AI could help identify people at higher risk of common cancers using routine health data