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 ...

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global ...

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, ...

To create their contactless approach, the researchers created a machine learning algorithm capable of analyzing aspects of ...

Researchers worked with the Federal Reserve to create a predictive model that assesses hundreds of institutional ...

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 ...

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

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