AIMC Topic: Humans

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Development of a Recommendation Engine to University Student Mental Health Support Aligned With Stepped Care: Longitudinal Cohort Study.

Journal of medical Internet research
BACKGROUND: Mental health challenges are prevalent among Canadian higher education students, with significant rates of depression and anxiety often going untreated due to reduced early detection, stigmatizing beliefs, and practical barriers. The U-Fl...

An improved artificial gorilla troops optimizer for BP neural network-based housing price prediction.

PloS one
In the context of global economic austerity in the post epidemic era, housing, as one of the basic human needs, has become particularly important for accurate prediction of house prices. BP neural network is widely used in prediction tasks, but their...

Predicting severe renal dysfunction in alcohol-associated cirrhosis: Comparative performance of liver function scores and machine learning models.

PloS one
BACKGROUND: Renal dysfunction is a frequent and clinically relevant complication of cirrhosis, yet chronic kidney disease (CKD) often remains underrecognized, particularly in non-acute settings. Early identification of at-risk patients is essential t...

Auto-Masked Audio Spectrogram Transformer for depression detection from speech.

Journal of affective disorders
BACKGROUND: Depression is a psychological disorder characterized by altered self-referential cognition and impaired emotional expression. Traditional diagnostic methods can be costly or intrusive, while Speech-based analysis offers an accessible alte...

Machine learning-assisted identification of core flavor compounds and prediction of core microorganisms in fermentation grains and pit mud during the fermentation process of strong-flavor Baijiu.

Food chemistry
The quality of strong-flavor Baijiu (SFB) is directly determined by key flavor compounds, which are influenced by microorganisms during fermentation. This study employed flavoromics and machine learning technologies to explore the relationship betwee...

AI-Validated Brain Targeted mRNA Lipid Nanoparticles with Neuronal Tropism.

ACS nano
Targeting therapeutic nanoparticles to the brain poses a challenge due to the restrictive nature of the blood-brain barrier (BBB). Here we report the development of mRNA-loaded lipid nanoparticles (LNPs) functionalized with BBB-interacting small mole...

A deep learning approach based on molecular graph features and residual blocks to predict interaction sites between CircRNA and RBP.

Biochemical and biophysical research communications
CircRNAs are ubiquitously expressed across diverse tissues and cells, playing a pivotal role not only in protein-mediated biological processes but also in disease prevention and therapeutics. RNA-RBP interactions are critical for deciphering gene reg...

From perceiving words to reading: Neural multivariate representations of sublexical vs. lexico-semantic processing during word-reading.

NeuroImage
While the neural underpinnings of semantic cognition have been extensively studied, the brain mechanisms that allow the extraction of meaning from the initially perceptual visual linguistic input are less understood. These mechanisms have typically b...

Machine Learning Navigated Allosteric Network to Unveil Biased Allosteric Modulation of GPCRs.

Journal of chemical theory and computation
Biased allosteric modulators (BAMs) offer a promising avenue for developing safer and more selective therapeutics for G protein-coupled receptors (GPCRs). However, their molecular mechanisms remain unclear due to the complex combination of biased and...

DGSS: A Dynamic Interaction Graph Neural Network with Specific Substructure Awareness for Drug Synergy Prediction.

Journal of chemical information and modeling
Combination therapy presents a transformative approach to treating complex diseases such as cancer by mitigating toxicity and resistance challenges inherent to monotherapy. A critical gap in current computational methods, however, lies in their inabi...