New framework renders AI more trustworthy for cancer subtyping

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

A Graph Neural Network based fMRI classification

Abstract: In this paper, we aim to describe a novel deep learning model (a machine learning subclass) to classify fMRI. We used a publicly available dataset to train and test the model which involved ...
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 ...
Frontiers

High-accuracy lung sound classification for healthy versus unhealthy diagnosis using artificial neural network

In recent years, advancements in machine learning and electronic stethoscope technology have enabled high-precision recording and analysis of lung sounds, significantly enhancing pulmonary disease ...
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 ...
C&EN

Interpretable Multiscale Convolutional Neural Network for Classification and Feature Visualization of Weak Raman Spectra of Biomolecules at Cell Membranes

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Raman spectroscopy in biological applications faces challenges due to complex spectra, ...
Scientific Research Publishing

Elfwing, S., Uchibe, E. and Doya, K. (2015) Expected Energy-Based Restricted Boltzmann Machine for Classification. Neural Networks, 64, 29-38.

ABSTRACT: The rapid growth of technology impacts all aspects of modern life, including banking and financial transactions. While these industries benefit significantly from technological advancements, ...