New framework renders AI more trustworthy for cancer subtyping

Medical artificial intelligence (AI) faces a fundamental challenge: uncertainty quantification. Artificial neural networks ...

Researchers develop new 'emotionally aware' model for classifying mental health conditions

Researchers have developed a new "emotionally aware" AI-based model for classifying mental health conditions, which could ...
Frontiers

Evolutionary algorithm-optimized feature fusion for accurate classification of shredded tobacco using multi-sensor data

Individual sensor systems have limitations in the complex task of classifying shredded tobacco. This study aims to overcome these limitations by developing a novel evolutionary algorithm-based feature ...
Nature

A supported decision-making model for idiopathic pulmonary fibrosis based on feature screening and optimized neural network

Idiopathic pulmonary fibrosis (IPF) severely impairs human respiratory function, with an increasing incidence and mortality. Treatment based on syndrome differentiation is the characteristics and ...
GitHub

What are neural networks?

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 ...
Nature

Optimized extreme learning machines with deep learning for high-performance network traffic classification

The exponential growth in network users and applications, coupled with increasing dependence on networked systems, has elevated network security to a paramount concern for service providers and ...
Bleeping Computer

MATLAB dev says ransomware gang stole data of 10,000 people

MathWorks, a leading developer of mathematical simulation and computing software, revealed that a ransomware gang stole the data of over 10,000 people after breaching its network in April. The company ...
IEEE

Behavioral Classification of Sequential Neural Activity Using Time Varying Recurrent Neural Networks

Abstract: Shifts in data distribution across time can strongly affect early classification of time-series data. When decoding behavior from neural activity, early detection of behavior may help in ...
Frontiers

Automated classification of midpalatal suture maturation using 2D convolutional neural networks on CBCT scans

Accurate assessment of midpalatal suture (MPS) maturation is critical in orthodontics, particularly for planning treatment strategies in patients with maxillary transverse deficiency (MTD). Although ...
Everyday Health

What's the Difference Between In-Network and Out-of-Network?

If you have a health insurance plan, you’ve probably come across the terms “in-network” and “out-of-network.” Simply put, in-network means the doctors or hospitals you visit contract with your ...
NBC News

'Ghost networks' are harming patients, but attempts to eliminate them have fallen short

The clock started ticking when Michelle Mazzola’s son, Guy, was diagnosed with autism before his second birthday. Doctors told her the sooner Guy received therapy for his nonverbal communication and ...
Live Science

What are neural processing units (NPUs) and why are they so important to modern computing?

Yet for neural networks to regain their foothold as a respected part of computer science, it took the success of speech recognition in the early 2000s., Even then, LeCun said: “We didn’t want to use ...