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

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 ...

For the first time, researchers have used machine learning—a type of artificial intelligence (AI)—to identify the most ...

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

Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care This study aims to investigate the impact of ...

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

TrialTranslator uncovers the survival gap for high-risk patients and offers a path to better cancer research. Study: Evaluating generalizability of oncology trial results to real-world patients using ...