AIMC Topic: Young Adult

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Machine learning based classification of catastrophic health expenditures: a cross-sectional study of Korean low-income households.

BMC health services research
BACKGROUND: Despite the National Health Insurance (NHI) system implemented in South Korea, concerns persist regarding access to health coverage for low-income households. To address this issue, this study aims to use machine learning-based data minin...

Explainable illicit drug abuse prediction using hematological differences.

Scientific reports
This study aimed to develop a reliable and explainable predictive model for illicit drug use (IDU). The model uses a machine learning (ML) algorithm to predict IDU using hematological differences between illicit drug users (IDUr) and non-users (n-IDU...

Machine learning derived development and validation of extracellular matrix related signature for predicting prognosis in adolescents and young adults glioma.

Scientific reports
The mortality rates have been increasing for glioma in adolescents and young adults (AYAs, aged 15-39 years). However, current biomarkers for clinical assessment in AYAs glioma are limited, prompting the urgent need for identifying ideal prognostic s...

Comparison of machine learning models for mucopolysaccharidosis early diagnosis using UAE medical records.

Scientific reports
Rare diseases, such as Mucopolysaccharidosis (MPS), present significant challenges to the healthcare system. Some of the most critical challenges are the delay and the lack of accurate disease diagnosis. Early diagnosis of MPS is crucial, as it has t...

Invulnerability bias in perceptions of artificial intelligence's future impact on employment.

Scientific reports
The adoption of Artificial Intelligence (AI) is reshaping the labor market; however, individuals' perceptions of its impact remain inconsistent. This study investigates the presence of the Invulnerability Bias (IB), where workers perceive that AI wil...

Non-invasive acoustic classification of adult asthma using an XGBoost model with vocal biomarkers.

Scientific reports
Traditional diagnostic methods for asthma, a widespread chronic respiratory illness, are often limited by factors such as patient cooperation with spirometry. Non-invasive acoustic analysis using machine learning offers a promising alternative for ob...

Predict the writer's trait emotional intelligence from reproduced calligraphy.

Scientific reports
Trait emotional intelligence (EI) describes an individual's ability to control their emotions. In Chinese calligraphy, there is a saying that "the character reflects the person." This raises a hypothesis: is it possible to predict a writer's trait EI...

Neural Synchrony and Consumer Behavior: Predicting Friends' Behavior in Real-World Social Networks.

The Journal of neuroscience : the official journal of the Society for Neuroscience
The endogenous aspect of social influence, reflected in the spontaneous alignment of behaviors within close social relationships, plays a crucial role in understanding human social behavior. In two studies involving 222 human subjects (Study 1:  = 17...

Neural Signals-Based Respiratory Motion Tracking: A Surface Electromyography Study.

International journal of radiation oncology, biology, physics
PURPOSE: Neural signals-based respiratory motion tracking offers a potential solution to the system latency issue of medical linear accelerators in respiratory motion tracking radiation therapy. However, decoding respiratory-related neural signals fr...

Altered effective connectivity in patients with drug-naïve first-episode, recurrent, and medicated major depressive disorder: A multi-site fMRI study.

Behavioural brain research
BACKGROUND: Major depressive disorder (MDD) has been diagnosed through subjective and inconsistent clinical assessments. Resting-state functional magnetic resonance imaging (rs-fMRI) with connectivity analysis has been valuable for identifying neural...