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Socioeconomic Factors

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Use of natural language processing to improve predictive models for imaging utilization in children presenting to the emergency department.

BMC medical informatics and decision making
OBJECTIVE: To examine the association between the medical imaging utilization and information related to patients' socioeconomic, demographic and clinical factors during the patients' ED visits; and to develop predictive models using these associated...

Potential Confounders in the Analysis of Brazilian Adolescent's Health: A Combination of Machine Learning and Graph Theory.

International journal of environmental research and public health
The prevalence of health problems during childhood and adolescence is high in developing countries such as Brazil. Social inequality, violence, and malnutrition have strong impact on youth health. To better understand these issues we propose to combi...

Implementation of artificial intelligence in medicine: Status analysis and development suggestions.

Artificial intelligence in medicine
The general public's attitudes, demands, and expectations regarding medical AI could provide guidance for the future development of medical AI to satisfy the increasing needs of doctors and patients. The objective of this study is to investigate publ...

A deep learning model for pediatric patient risk stratification.

The American journal of managed care
OBJECTIVES: Current models for patient risk prediction rely on practitioner expertise and domain knowledge. This study presents a deep learning model-a type of machine learning that does not require human inputs-to analyze complex clinical and financ...

Applications of machine learning techniques to predict filariasis using socio-economic factors.

Epidemiology and infection
Filariasis is one of the major public health concerns in India. Approximately 600 million people spread across 250 districts of India are at risk of filariasis. To predict this disease, a pilot scale study was carried out in 30 villages of Karimnagar...

Prodromal clinical, demographic, and socio-ecological correlates of asthma in adults: a 10-year statewide big data multi-domain analysis.

The Journal of asthma : official journal of the Association for the Care of Asthma
To identify prodromal correlates of asthma as compared to chronic obstructive pulmonary disease and allied-conditions (COPDAC) using a multi domain analysis of socio-ecological, clinical, and demographic domains. This is a retrospective case-risk-co...

Applying machine learning approaches to analyze the vulnerable road-users' crashes at statewide traffic analysis zones.

Journal of safety research
INTRODUCTION: In this paper, we present machine learning techniques to analyze pedestrian and bicycle crash by developing macro-level crash prediction models.

Predicting coronary artery disease: a comparison between two data mining algorithms.

BMC public health
BACKGROUND: Cardiovascular diseases (CADs) are the first leading cause of death across the world. World Health Organization has estimated that morality rate caused by heart diseases will mount to 23 million cases by 2030. Hence, the use of data minin...

An ensemble learning method for asthma control level detection with leveraging medical knowledge-based classifier and supervised learning.

Journal of medical systems
Approximately 300 million people are afflicted with asthma around the world, with the estimated death rate of 250,000 cases, indicating the significance of this disease. If not treated, it can turn into a serious public health problem. The best metho...

Measuring social, environmental and health inequalities using deep learning and street imagery.

Scientific reports
Cities are home to an increasing majority of the world's population. Currently, it is difficult to track social, economic, environmental and health outcomes in cities with high spatial and temporal resolution, needed to evaluate policies regarding ur...