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Health Behavior

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Prediction models to identify individuals at risk of metabolic syndrome who are unlikely to participate in a health intervention program.

International journal of medical informatics
OBJECTIVES: Since the launch of a nationwide general health check-up and instruction program in Japan in 2008, interest in strategies to improve implementation of the program based on predictive analytics has grown. We investigated the performance of...

Efficient Active Sensing with Categorized Further Explorations for a Home Behavior-Monitoring Robot.

Journal of healthcare engineering
Mobile robotics is a potential solution to home behavior monitoring for the elderly. For a mobile robot in the real world, there are several types of uncertainties for its perceptions, such as the ambiguity between a target object and the surrounding...

The Human Behaviour-Change Project: harnessing the power of artificial intelligence and machine learning for evidence synthesis and interpretation.

Implementation science : IS
BACKGROUND: Behaviour change is key to addressing both the challenges facing human health and wellbeing and to promoting the uptake of research findings in health policy and practice. We need to make better use of the vast amount of accumulating evid...

Applying Deep Learning to Understand Predictors of Tooth Mobility Among Urban Latinos.

Studies in health technology and informatics
We applied deep learning algorithms to build correlate models that predict tooth mobility in a convenience sample of urban Latinos. Our application of deep learning identified age, general health, soda consumption, flossing, financial stress, and yea...

Intelligent judgements over health risks in a spatial agent-based model.

International journal of health geographics
BACKGROUND: Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adap...

Patterns and correlates of physical activity in adult Norwegians: a forecasted evolution up to 2025 based on machine learning approach.

BMC public health
BACKGROUND: As other westerns countries, a large portion of Norwegians do not meet the minimum recommendations for weekly physical activity (PA). One of the primary targets of the WHO's Global action plan for the prevention and control of noncommunic...

The Association of Urban Greenness and Walking Behavior: Using Google Street View and Deep Learning Techniques to Estimate Residents' Exposure to Urban Greenness.

International journal of environmental research and public health
Many studies have established that urban greenness is associated with better health outcomes. Yet most studies assess urban greenness with overhead-view measures, such as park area or tree count, which often differs from the amount of greenness perce...

Connectionism and Behavioral Clusters: Differential Patterns in Predicting Expectations to Engage in Health Behaviors.

Annals of behavioral medicine : a publication of the Society of Behavioral Medicine
BACKGROUND: The traditional approach to health behavior research uses a single model to explain one behavior at a time. However, health behaviors are interrelated and different factors predict certain behaviors better than others.

Unhealthy Behaviors, Prevention Measures, and Neighborhood Cardiovascular Health: A Machine Learning Approach.

Journal of public health management and practice : JPHMP
This study identifies and ranks predictors of cardiovascular health at the neighborhood level in the United States. We merged the 500 Cities Data and the 2011-2015 American Community Survey to create a new data set that includes sociodemographic char...

A Machine-Learning Approach to Predicting Smoking Cessation Treatment Outcomes.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
AIMS: Most cigarette smokers want to quit smoking and more than half make an attempt every year, but less than 10% remain abstinent for at least 6 months. Evidence-based tobacco use treatment improves the likelihood of quitting, but more than two-thi...