According to KXAN, Patel's system involves the usage of machine learning. It looks at what countries put in monetarily to ...

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

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

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

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

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.

n this study, 773 untreated breast cancer patients from all over China were collected and followed up for at least 5 years. We obtained clinical data from 773 cases, RNA sequencing data from 752 cases ...

AI and machine learning are revolutionizing drug discovery, development, and lifecycle management, addressing industry ...