A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.

This retrospective study included 643 patients who had undergone NSCLC resection. ML models (random forest, gradient boosting, extreme gradient boosting, and AdaBoost) and a random survival forest ...

A new study presented at the International Association for the Study of Lung Cancer 2025 World Conference on Lung Cancer (WCLC) validates the use of Sybil, a deep learning artificial intelligence ...

OAK BROOK, Ill. – An artificial intelligence (AI) deep learning tool that estimates the malignancy risk of lung nodules achieved high cancer detection rates while significantly reducing false-positive ...

Find out how machine learning identifies country-specific health system drivers shaping global cancer survival and highlights ...

UT biochemistry major Milit Patel collaborated with researchers at Memorial Sloan Kettering Cancer Center on research published in a top cancer journal.

For the first time, researchers have used machine learning – a type of artificial intelligence (AI) – to identify the most important drivers of cancer survival in nearly all the countries in the world ...