AIMC Topic: Young Adult

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Identifying and predicting dietary patterns in the Dutch population using machine learning.

European journal of nutrition
PURPOSE: Nutritional epidemiological research is shifting its focus from individual nutrients to dietary patterns, which challenges traditional statistical methods. Here, we aim to apply various machine learning algorithms to identify and predict die...

Personalized real-time inference of momentary excitability from human EEG.

NeuroImage
The efficacy of transcranial magnetic stimulation (TMS) is often limited by non-adaptive protocols that disregard instantaneous brain states, potentially constraining therapeutic outcomes. Current EEG-guided approaches are hindered by their reliance ...

Re-examining the association between region-specific pain recurrence and muscle force strategies in patients with patellofemoral pain via OpenSim and artificial intelligence: a prospective cohort study toward targeted rehabilitation.

Journal of neuroengineering and rehabilitation
BACKGROUND: This study utilized artificial intelligence (AI)-based machine learning algorithms, alongside the shapley additive explanations (SHAP) framework, to identify lower-limb muscle force patterns associated with recurrent patellofemoral pain (...

Differentiation of optic disc edema and pseudopapilledema with deep learning on near-infrared reflectance images.

BMC ophthalmology
BACKGROUND: This study aimed to develop an artificial intelligence-based deep learning (DL) algorithm using near-infrared reflectance (NIR) images to differentiate between optic disc edema and pseudopapilledema, and to evaluate the diagnostic perform...

Generative artificial intelligence models outperform students on divergent and convergent thinking assessments.

Scientific reports
Generative artificial intelligence (GenAI) has garnered significant attention for its remarkable capabilities and is now widely used in many creative domains, sparking scientific interest in its creative capacities. While previous studies have assess...

Predicting visual aesthetic preferences in Tehran city universities campuses using machine learning techniques.

Scientific reports
Visual aesthetic preferences fundamentally shape the restorative potential of university landscapes and have a significant impact on student well-being and engagement. This study developed Ensemble Learning Models to predict students' aesthetic prefe...

Advancing sleep health equity through deep learning on large-scale nocturnal respiratory signals.

Nature communications
Sleep disorders affect billions globally, yet diagnostic access remains limited by healthcare resource constraints. Here, we develop a deep learning framework that analyzes respiratory signals for remote sleep health monitoring, trained on 15,785 nig...

Sequential temporal anticipation characterized by neural power modulation and in recurrent neural networks.

eLife
Relevant prospective moments arise intermittently, while most of the time is filled with irrelevant events, or noise, that constantly bombard our sensory systems. Thus, anticipating a few key moments necessitates disregarding what lies between the pr...

Forewarned Is Forearmed: The Single- and Dual-Brain Mechanisms in Detectors from Dyads of Varying Social Distance during Deceptive Outcome Evaluation.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Preventing deception requires understanding how lie detectors process social information across social distance. Although the outcomes of such information are crucial, how detectors evaluate gains or losses from close versus distant others remains un...

Effects of iron repletion on brain iron content, myelination, neural network activation, and cognition.

JCI insight
BACKGROUNDBlood donation increases the risk of iron deficiency, but its effect on brain iron, myelination, and neurocognition remains unclear.METHODSThis ancillary study enrolled 67 iron-deficient blood donors, 19-73 years of age, participating in a ...