AIMC Topic: Adult

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Unsupervised Accuracy Estimation for Brain-Computer Interfaces Based on Selective Auditory Attention Decoding.

IEEE transactions on bio-medical engineering
OBJECTIVE: Selective auditory attention decoding (AAD) algorithms process brain data such as electroencephalography to decode to which of multiple competing sound sources a person attends. Example use cases are neuro-steered hearing aids or communica...

Precision Symptom Phenotyping Identifies Early Clinical and Proteomic Predictors of Distinct COVID-19 Sequelae.

The Journal of infectious diseases
BACKGROUND: Post-COVID conditions (PCC) are difficult to characterize, diagnose, predict, and treat due to overlapping symptoms and poorly understood pathology. Identifying inflammatory profiles may improve clinical prognostication and trial endpoint...

Significant associations between high-risk sexual behaviors and enterotypes of gut microbiome in HIV-negative men who have sex with men.

mSphere
UNLABELLED: Gut microbiome of men who have sex with men (MSM) exhibits distinctive characteristics compared with general populations. The dysbiosis of the gut microbiome in MSM is also associated with the onset and evolution of HIV infection. Enterot...

Patient prioritization for pharmaceutical intervention in the hospital setting: a retrospective cross-sectional study.

The International journal of pharmacy practice
OBJECTIVES: Prioritization of patients requiring pharmaceutical intervention is critical given limited resources. Data from pharmacy software could be used to target patients. This retrospective cross-sectional study aimed to describe the method impl...

Developing a Two-Dimensional Size-Exclusion Liquid Chromatography Platform for Isolating the High-Quality Extracellular Vesicles to Predict and Evaluate Metabolic Improvement Outcomes of Sleeve Gastrectomy.

Analytical chemistry
The direct analysis of plasma exosomal components still presents significant challenges due to the interference of high concentrations of albumin, immunoglobulins, and other abundant proteins. Herein, we developed a two-dimensional size-exclusion liq...

A negative combined effect of exposure to maternal Mn-Cu-Rb-Fe metal mixtures on gestational anemia, and the mediating role of creatinine in the Guangxi Birth Cohort Study (GBCS): Twelve machine learning algorithms.

Ecotoxicology and environmental safety
The link between individual metals and gestational anemia has been established, but the impact of metal mixtures and the mediating role of renal function on gestational anemia remain inconclusive. The concentrations of 20 blood essential trace and no...

Predicting depression in healthy young adults: A machine learning approach using longitudinal neuroimaging data.

NeuroImage
Accurate prediction of depressive symptoms in healthy individuals can enable early intervention and reduce both individual and societal costs. This study aimed to develop predictive models for depression in young adults using machine learning (ML) te...

Decoding the Narcissistic Brain.

NeuroImage
There is a substantial knowledge gap in the narcissism literature: <1 % of the nearly 12,000 articles on narcissism have addressed its neural basis. To help fill this gap, we asked whether the multifacetedness of narcissism could be decoded from spon...

A Transformer-Based Framework for Counterfactual Estimation of Antihypertensive Treatment Effect on COVID-19 Infection Risk - A Proof-of-Concept Study.

American journal of hypertension
BACKGROUND: Transformer-based neural networks excel in modelling high-dimensional, time-series data with complex dependencies. This proof-of-concept study applies a transformer-X-learner framework to estimate treatment effects using real-world data, ...

Machine learning-driven risk prediction and feature identification for major depressive disorder and its progression: an exploratory study based on five years of longitudinal data from the US national health survey.

Journal of affective disorders
BACKGROUND: Major depressive disorder (MDD) presents significant public health challenges due to its increasing prevalence and complex risk factors. This study systematically analyzed data from 2019 to 2023 to explore trends in MDD incidence, symptom...