Advancing Superior Accuracy in Early Lung Cancer Detection Using Selective Metabolic Pathways and Data Enrichment for ...

Researchers at the University of Michigan developed a machine learning–based digital twin to map real-time tumor metabolism ...

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 ...

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

A new machine-learning-based approach to mapping real-time tumor metabolism in brain cancer patients, developed at the ...

A new machine-learning-based approach to mapping real-time tumor metabolism in brain cancer patients, developed at the ...

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

AI has revealed why cancer survival differs so dramatically around the world, highlighting the specific health system factors that matter most in each country.

Thyroid cancer is the most common endocrine cancer, affecting more people each year as detection rates continue to rise.