Mount Sinai analysis looks at the effectiveness of electrocardiograms analyzed via deep learning as a tool for early COPD detection ...

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality globally. Effective management ...

Nia Therapeutics has published peer-reviewed data in Brain Stimulation on the first in vivo validation of its wireless, ...

Abstract: The vast majority of published event-triggered mechanisms (ETMs) are constructed based on measurement errors, which introduces a problem naturally that they are updated when the measurement ...

What is a neural network? A neural network, also known as an artificial neural network, is a type of machine learning that works similarly to how the human brain processes information. Instead of ...

ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...

Pea-sized brains grown in a lab have for the first time revealed the unique way neurons might misfire due to schizophrenia and bipolar disorder, psychiatric ailments that affect millions of people ...

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...

For the uninitiated, every Soulslike feels like a steep learning curve defines it, but those in the know are well aware that there's a wide spectrum of Soulslike difficulty. Some of the most difficult ...

ABSTRACT: Predicting the material stability is essential for accelerating the discovery of advanced materials in renewable energy, aerospace, and catalysis. Traditional approaches, such as Density ...