AIMC Topic: Socioeconomic Factors
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Emergency department use and Artificial Intelligence in Pelotas: design and baseline results.
Revista brasileira de epidemiologia = Brazilian journal of epidemiology
Mar 10, 2023
OBJETIVO: To describe the initial baseline results of a population-based study, as well as a protocol in order to evaluate the performance of different machine learning algorithms with the objective of predicting the demand for urgent and emergency s...
Socioexposomics of COVID-19 across New Jersey: a comparison of geostatistical and machine learning approaches.
Journal of exposure science & environmental epidemiology
Feb 1, 2023
BACKGROUND: Disparities in adverse COVID-19 health outcomes have been associated with multiple social and environmental stressors. However, research is needed to evaluate the consistency and efficiency of methods for studying these associations at lo...
A deep learning model identifies emphasis on hard work as an important predictor of income inequality.
Scientific reports
Jun 14, 2022
High levels of income inequality can persist in society only if people accept the inequality as justified. To identify psychological predictors of people's tendency to justify inequality, we retrained a pre-existing deep learning model to predict the...
Prediction of Labor Unemployment Based on Time Series Model and Neural Network Model.
Computational intelligence and neuroscience
Jun 3, 2022
With the advent of big data, statistical accounting based on artificial intelligence can realistically reflect the dynamics of labor force and market segmentation. Therefore, based on the combination of machine learning algorithm and traditional stat...
Use of a deep learning and random forest approach to track changes in the predictive nature of socioeconomic drivers of under-5 mortality rates in sub-Saharan Africa.
BMJ open
Feb 17, 2022
OBJECTIVES: We used machine learning algorithms to track how the ranks of importance and the survival outcome of four socioeconomic determinants (place of residence, mother's level of education, wealth index and sex of the child) of under-5 mortality...
Water tank and swimming pool detection based on remote sensing and deep learning: Relationship with socioeconomic level and applications in dengue control.
PloS one
Dec 9, 2021
Studies have shown that areas with lower socioeconomic standings are often more vulnerable to dengue and similar deadly diseases that can be spread through mosquitoes. This study aims to detect water tanks installed on rooftops and swimming pools in ...
Drivers and social implications of Artificial Intelligence adoption in healthcare during the COVID-19 pandemic.
PloS one
Nov 22, 2021
The COVID-19 pandemic continues to impact people worldwide-steadily depleting scarce resources in healthcare. Medical Artificial Intelligence (AI) promises a much-needed relief but only if the technology gets adopted at scale. The present research in...
Comparing COVID-19 risk factors in Brazil using machine learning: the importance of socioeconomic, demographic and structural factors.
Scientific reports
Aug 2, 2021
The COVID-19 pandemic continues to have a devastating impact on Brazil. Brazil's social, health and economic crises are aggravated by strong societal inequities and persisting political disarray. This complex scenario motivates careful study of the c...
Augmented intelligence to predict 30-day mortality in patients with cancer.
Future oncology (London, England)
Jun 30, 2021
An augmented intelligence tool to predict short-term mortality risk among patients with cancer could help identify those in need of actionable interventions or palliative care services. An algorithm to predict 30-day mortality risk was developed us...
Using machine learning to examine street green space types at a high spatial resolution: Application in Los Angeles County on socioeconomic disparities in exposure.
The Science of the total environment
May 8, 2021
BACKGROUND: Compared to commonly-used green space indicators from downward-facing satellite imagery, street view-based green space may capture different types of green space and represent how environments are perceived and experienced by people on th...
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