AIMC Topic: Humans

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Mapping Algorithmic Bias in AI-Powered Electrocardiogram Interpretation Across the AI Life Cycle: Protocol for a Scoping Review.

JMIR research protocols
BACKGROUND: Artificial intelligence (AI)-powered analysis of electrocardiograms (ECGs) is reshaping cardiac diagnostics, offering faster and often more accurate detection of conditions such as arrhythmias and heart failure. However, growing evidence ...

Autonomous conversational agents for loneliness, social isolation, depression, and anxiety in older people without cognitive impairment: Systematic review and meta-analysis.

Psychological medicine
Loneliness is a major psychological challenge in older adulthood, contributing to increased risks of depression, anxiety, and mortality. Conversational agents - technologies that interact with users via natural language - have emerged as potential to...

CTSSP: A temporal-spectral-spatial joint optimization algorithm for motor imagery EEG decoding.

Journal of neural engineering
Objective.Motor imagery brain-computer interfaces hold significant promise for neurorehabilitation, yet their performance is often compromised by electroencephalography (EEG) non-stationarity, low signal-to-noise ratios, and severe cross-session vari...

Biofabrication of 3D bioprinted and organ-on-chip blood-brain barrier models using hCMEC/D3 for intranasal delivery of central nervous system therapeutics.

Biofabrication
The BBB remains a major obstacle to effective treatment of CNS disorders by limiting the entry of most therapeutics into the brain. The hCMEC/D3 is widely used as anin vitromodel to study BBB structure, permeability, and drug transport. In parallel, ...

Automated 3D segmentation of human vagus nerve fascicles and epineurium from micro-computed tomography images using anatomy-aware neural networks.

Journal of neural engineering
Objective.Precise segmentation and quantification of nerve morphology from imaging data are critical for designing effective and selective peripheral nerve stimulation (PNS) therapies. However, prior studies on nerve morphology segmentation suffer fr...

Investigating the relationship between teacher efficacy, job satisfaction, and digital resource utilization in assessment practices: Insights from PISA 2018 and 2022.

PloS one
The COVID-19 pandemic disrupted global education systems, forcing rapid shifts in teaching practices, technology integration, and assessment methods. However, little is known about how teacher efficacy, job satisfaction, and digital adoption vary acr...

Reassessing feature-based Android malware detection in a contemporary context.

PloS one
We report the findings of a reimplementation of 18 foundational studies in feature-based machine learning for Android malware detection, published during the period 2013-2023. These studies are reevaluated on a level playing field using a contemporar...

Federated TriNet-AQ: Explainable english proficiency classification in augmented and virtual reality learning.

PloS one
AR/VR and other immersive technologies are creating dynamic, learner-centred, and engaging language-learning environments. In these ever-changing situations, judging someone's language abilities is difficult. Managing multimodal learner inputs, under...

FetCAT: Cross-attention fusion of transformer-CNN architecture for fetal brain plane classification with explainability using motion-degraded MRI.

PloS one
Fetal brain magnetic resonance imaging (MRI) has been recognized as a vital diagnostic tool for identifying neurological anomalies during pregnancy. Accurate classification of fetal MRI planes is essential for effective prenatal neurological assessme...

Semantic code clone detection using hybrid intermediate representations and BiLSTM networks.

PloS one
Semantic code clone detection plays an essential role in software maintenance and quality assurance, as it helps uncover fragments of code that express the same logic even when their syntax has been altered or deliberately obfuscated. In this study, ...