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[Relationship between certain uses of artificial intelligence and psychosocial risk factors in European work environments].

Archivos de prevencion de riesgos laborales Jul 15, 2024
INTRODUCTION: To examine the relationship between the use of Artificial Intelligence (AI) to assess and monitor job performance and exposure to psychosocial risk factors, as well as associated adverse health effects in the European work environment.
Cross-Sectional Studies Male Middle Aged Europe Artificial Intelligence Workload Workplace Occupational Health Female Risk Factors Occupational Stress Young Adult Working Conditions Adult Humans
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GMAC-A Simple Measure to Quantify Upper Limb Use From Wrist-Worn Accelerometers.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jul 15, 2024
Various measures have been proposed to quantify upper-limb use through wrist-worn inertial measurement units. The two most popular traditional measures of upper-limb use - thresholded activity counts (TAC) and the gross movement (GM) score suffer fro...
Algorithms Female Reproducibility of Results Young Adult Male Wearable Electronic Devices Wrist Adult Sensitivity and Specificity Humans Machine Learning Accelerometry Movement Upper Extremity
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Identifying high-risk Fontan phenotypes using K-means clustering of cardiac magnetic resonance-based dyssynchrony metrics.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Jul 14, 2024
BACKGROUND: Individuals with a Fontan circulation encompass a heterogeneous group with adverse outcomes linked to ventricular dilation, dysfunction, and dyssynchrony. The purpose of this study was to assess if unsupervised machine learning cluster an...
Magnetic Resonance Imaging, Cine Myocardial Contraction Image Interpretation, Computer-Assisted Adult Heart Transplantation Biomechanical Phenomena Fontan Procedure Humans Male Heart Defects, Congenital Phenotype Ventricular Function, Left Retrospective Studies Treatment Outcome Risk Assessment Female Unsupervised Machine Learning Cluster Analysis Adolescent Risk Factors Predictive Value of Tests Time Factors Young Adult Ventricular Dysfunction, Left Child
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Paediatric nurses' perspectives on artificial intelligence applications: A cross-sectional study of concerns, literacy levels and attitudes.

Journal of advanced nursing Jul 14, 2024
AIMS: This study aimed to explore the correlation between artificial intelligence (AI) literacy, AI anxiety and AI attitudes among paediatric nurses, as well as identify the influencing factors on paediatric nurses' AI attitudes.
Female Young Adult Adult Cross-Sectional Studies Male Humans Artificial Intelligence Pediatric Nursing Middle Aged Nurses, Pediatric Surveys and Questionnaires Attitude of Health Personnel Turkey
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Comparing human evaluations of eyewitness statements to a machine learning classifier under pristine and suboptimal lineup administration procedures.

Cognition Jul 14, 2024
Recent work highlights the ability of verbal machine learning classifiers to distinguish between accurate and inaccurate recognition memory decisions (Dobbins, 2022; Dobbins & Kantner, 2019; Seale-Carlisle, Grabman, & Dodson, 2022). Given the surge o...
Young Adult Adult Male Judgment Humans Machine Learning Female Mental Recall Recognition, Psychology
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Identification and diagnosis of schizophrenia based on multichannel EEG and CNN deep learning model.

Schizophrenia research Jul 14, 2024
This paper proposes a high-accuracy EEG-based schizophrenia (SZ) detection approach. Unlike comparable literature studies employing conventional machine learning algorithms, our method autonomously extracts the necessary features for network training...
Female Young Adult Adult Male Signal Processing, Computer-Assisted Schizophrenia Humans Neural Networks, Computer Deep Learning Electroencephalography
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State-of-the-art sleep arousal detection evaluated on a comprehensive clinical dataset.

Scientific reports Jul 14, 2024
Aiming to apply automatic arousal detection to support sleep laboratories, we evaluated an optimized, state-of-the-art approach using data from daily work in our university hospital sleep laboratory. Therefore, a machine learning algorithm was traine...
Arousal Middle Aged Adolescent Predictive Value of Tests Area Under Curve Statistics, Nonparametric Polysomnography Sleep Wake Disorders Sleep Datasets as Topic Aged, 80 and over Young Adult Adult Male Humans Machine Learning Female Aged
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Functional Near-Infrared Spectroscopy-Based Computer-Aided Diagnosis of Major Depressive Disorder Using Convolutional Neural Network with a New Channel Embedding Layer Considering Inter-Hemispheric Asymmetry in Prefrontal Hemodynamic Responses.

Depression and anxiety Jul 14, 2024
BACKGROUND: Functional near-infrared spectroscopy (fNIRS) is being extensively explored as a potential primary screening tool for major depressive disorder (MDD) because of its portability, cost-effectiveness, and low susceptibility to motion artifac...
Spectroscopy, Near-Infrared Adult Humans Prefrontal Cortex Convolutional Neural Networks Male Hemodynamics Middle Aged Neural Networks, Computer Diagnosis, Computer-Assisted Deep Learning Depressive Disorder, Major Female Functional Neuroimaging Young Adult
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The neural network RTNet exhibits the signatures of human perceptual decision-making.

Nature human behaviour Jul 12, 2024
Convolutional neural networks show promise as models of biological vision. However, their decision behaviour, including the facts that they are deterministic and use equal numbers of computations for easy and difficult stimuli, differs markedly from ...
Male Decision Making Reaction Time Visual Perception Neural Networks, Computer Female Young Adult Adult Humans
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Medical intelligence using PPG signals and hybrid learning at the edge to detect fatigue in physical activities.

Scientific reports Jul 12, 2024
The educational environment plays a vital role in the development of students who participate in athletic pursuits both in terms of their physical health and their ability to detect fatigue. As a result of recent advancements in deep learning and bio...
Humans Exercise Deep Learning Photoplethysmography Signal Processing, Computer-Assisted Fatigue Neural Networks, Computer Female Young Adult Male
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