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Socioeconomic Factors

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Clinical and socioeconomic predictors of hospital use and emergency department visits among children with medical complexity: A machine learning approach using administrative data.

PloS one
OBJECTIVES: The primary objective of this study was to identify clinical and socioeconomic predictors of hospital and ED use among children with medical complexity within 1 and 5 years of an initial discharge between 2010 and 2013. A secondary object...

Machine learning analysis of the effects of COVID-19 on migration patterns.

Scientific reports
This study investigates the impact of the COVID-19 pandemic on European tourist mobility patterns from 2019 to 2021 by conceptualizing countries as monomers emitting radiation to model and analyze their patterns through the lens of socio-economics an...

Social Robots and Sensors for Enhanced Aging at Home: Mixed Methods Study With a Focus on Mobility and Socioeconomic Factors.

JMIR aging
BACKGROUND: Population aging affects society, with a profound impact on daily activities for those of a low socioeconomic status and with motor impairments. Social assistive robots (SARs) and monitoring technologies can improve older adults' well-bei...

How sociodemographic factors relate to trust in artificial intelligence among students in Poland and the United Kingdom.

Scientific reports
The article aims to determine the sociodemographic factors associated with the level of trust in artificial intelligence (AI) based on cross-sectional research conducted in late 2023 and early 2024 on a sample of 2098 students in Poland (1088) and th...

Sociodemographic bias in clinical machine learning models: a scoping review of algorithmic bias instances and mechanisms.

Journal of clinical epidemiology
BACKGROUND AND OBJECTIVES: Clinical machine learning (ML) technologies can sometimes be biased and their use could exacerbate health disparities. The extent to which bias is present, the groups who most frequently experience bias, and the mechanism t...

Psychological predictors of socioeconomic resilience amidst the COVID-19 pandemic: Evidence from machine learning.

The American psychologist
What predicts cross-country differences in the recovery of socioeconomic activity from the COVID-19 pandemic? To answer this question, we examined how quickly countries' socioeconomic activity bounced back to normalcy from disruptions caused by the C...

Mapping Spatiotemporal Disparities in Residential Electricity Inequality Using Machine Learning.

Environmental science & technology
The move toward electrification is critical for decarbonizing the energy sector but may exacerbate energy unaffordability without proper safeguards. Addressing this challenge requires capturing neighborhood-scale dynamics to uncover the blind spots i...

Development of Machine Learning Algorithms for Identifying Patients With Limited Health Literacy.

Journal of evaluation in clinical practice
RATIONALE: Limited health literacy (HL) leads to poor health outcomes, psychological stress, and misutilization of medical resources. Although interventions aimed at improving HL may be effective, identifying patients at risk of limited HL in the cli...

Exploring key factors influencing depressive symptoms among middle-aged and elderly adult population: A machine learning-based method.

Archives of gerontology and geriatrics
OBJECTIVE: This paper aims to investigate the key factors, including demographics, socioeconomics, physical well-being, lifestyle, daily activities and loneliness that can impact depressive symptoms in the middle-aged and elderly population using mac...

Haves and have-nots: socioeconomic position improves accuracy of machine learning algorithms for predicting high-impact chronic pain.

Pain
Lower socioeconomic position (SEP) is associated with increased risk of developing chronic pain, experiencing more severe pain, and suffering greater pain-related disability. However, SEP is a multidimensional construct; there is a dearth of research...