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

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

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

Competing machine-learning algorithms To predict the time of death, the model uses an array of clinical information from the donor including gender, age, body mass index, blood pressure, heart rate, ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...

A urosepsis prediction model based on 6 factors demonstrated strong performance among a Chinese cohort. A large-scale study of 33,579 urinary stones from Southern China, published in the International ...

More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...