Machine learning finds four behavior symptom profiles tied to early dementia processes

Behavioral changes—such as anxiety, depression, irritability, apathy or agitation, collectively known as neuropsychiatric ...

Researchers detect complex emotions by combining multiple optical signals

Researchers have developed a new way to recognize human emotions by combining fiber-based physiological signals with thermal ...
Scientific Research Publishing

An Empirical Study Based on Big Data Analysis to Analyze Social Media Group Sentiment and Its Impact on Consumer Psychology ()

As social media becomes the core domain of information interaction in the era of big data, the emotional information contained in the vast amount of user-generated content provides an unprecedented ...
Cyber Defense Magazine

Deepfakes, Synthetic Media, and Digital Trust: The Cybersecurity Implications of Deepfake Technology and Methods for Detection and Mitigation

Introduction The proliferation of deepfake technology, synthetic media generated using advanced artificial intelligence techniques, has emerged as a ...
Frontiers

RS-STGCN: Regional-Synergy Spatio-Temporal Graph Convolutional Network for emotion recognition

Decoding emotional states from electroencephalography (EEG) signals is a fundamental goal in affective neuroscience. This endeavor requires accurately modeling the complex spatio-temporal dynamics of ...
IEEE

Speech Emotion Recognition using Machine Learning

Abstract: The aim of the paper is to detect the emotions which are elicited by the speaker while speaking. Emotion Detection has become a essential task these days. The speech which is in fear, anger, ...
Frontiers

Speech analysis and speech emotion recognition in mental disease: a scoping review

Mental disorders have a significant impact on many areas of people’s life, particularly on affective regulation; thus, there is a growing need to find disease-specific biomarkers to improve early ...
pv magazine International

Machine learning-based fault detection technique for bifacial PV

A research team led by the University of Sharjah in the United Arab Emirates has developed a novel machine learning approach for fault detection in bifacial PV systems. The method combines a ...
ahajournals.org

Abstract Fri013: AI-Driven Gait Classification for Peripheral Artery Disease (PAD) Detection Using Machine Learning and Nonlinear Gait Dynamics

Introduction: Peripheral Artery Disease (PAD) is a progressive vascular disorder impairing mobility, raising fall risk, and reducing quality of life. Early detection is key to preventing amputations ...