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

Researchers developed a machine learning model that could identify children in the ED who were at risk for developing sepsis ...

In this retrospective cohort analysis, researchers aimed to identify key predictors of trial enrollment among cancer patients.

Background Prehospital delays remain critical barriers to timely acute coronary syndrome (ACS) care, particularly for ...

The presented findings are important for the field of cell-cycle control. They provide new insights into the origin of cell size variability in budding yeast. The strength of evidence is solid.