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Socioeconomic Factors

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Measures of socioeconomic advantage are not independent predictors of support for healthcare AI: subgroup analysis of a national Australian survey.

BMJ health & care informatics
Applications of artificial intelligence (AI) have the potential to improve aspects of healthcare. However, studies have shown that healthcare AI algorithms also have the potential to perpetuate existing inequities in healthcare, performing less effe...

Predicting the effect of confinement on the COVID-19 spread using machine learning enriched with satellite air pollution observations.

Proceedings of the National Academy of Sciences of the United States of America
The real-time monitoring of reductions of economic activity by containment measures and its effect on the transmission of the coronavirus (COVID-19) is a critical unanswered question. We inferred 5,642 weekly activity anomalies from the meteorology-a...

Early Prediction of Gestational Diabetes Mellitus in the Chinese Population via Advanced Machine Learning.

The Journal of clinical endocrinology and metabolism
CONTEXT: Accurate methods for early gestational diabetes mellitus (GDM) (during the first trimester of pregnancy) prediction in Chinese and other populations are lacking.

Using machine learning to estimate the effect of racial segregation on COVID-19 mortality in the United States.

Proceedings of the National Academy of Sciences of the United States of America
This study examines the role that racial residential segregation has played in shaping the spread of COVID-19 in the United States as of September 30, 2020. The analysis focuses on the effects of racial residential segregation on mortality and infect...

Analysis of Risk Factors in Dementia Through Machine Learning.

Journal of Alzheimer's disease : JAD
BACKGROUND: Sociodemographic data indicate the progressive increase in life expectancy and the prevalence of Alzheimer's disease (AD). AD is raised as one of the greatest public health problems. Its etiology is twofold: on the one hand, non-modifiabl...

Reporting of demographic data and representativeness in machine learning models using electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The development of machine learning (ML) algorithms to address a variety of issues faced in clinical practice has increased rapidly. However, questions have arisen regarding biases in their development that can affect their applicability i...

Machine-learning prediction of unplanned 30-day rehospitalization using the French hospital medico-administrative database.

Medicine
Predicting unplanned rehospitalizations has traditionally employed logistic regression models. Machine learning (ML) methods have been introduced in health service research and may improve the prediction of health outcomes. The objective of this work...

Leveraging Machine Learning to Identify Predictors of Receiving Psychosocial Treatment for Attention Deficit/Hyperactivity Disorder.

Administration and policy in mental health
This study aimed to identify factors associated with receiving psychosocial treatment for ADHD in a nationally representative sample. Participants were 6630 youth with a parent-reported diagnosis of ADHD from the 2016-2017 National Survey of Children...