AIMC Topic: Health Behavior

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Tree-Based Machine Learning to Identify and Understand Major Determinants for Stroke at the Neighborhood Level.

Journal of the American Heart Association
Background Stroke is a major cardiovascular disease that causes significant health and economic burden in the United States. Neighborhood community-based interventions have been shown to be both effective and cost-effective in preventing cardiovascul...

Patients' Convergence of Mass and Interpersonal Communication on an Online Forum: Hybrid Methods Analysis.

Journal of medical Internet research
BACKGROUND: Patients are increasingly taking an active role in their health. In doing so, they combine both mass and interpersonal media to gratify their cognitive and affective needs (ie, convergence). Owing to methodological challenges when studyin...

The Current Research Landscape of the Application of Artificial Intelligence in Managing Cerebrovascular and Heart Diseases: A Bibliometric and Content Analysis.

International journal of environmental research and public health
The applications of artificial intelligence (AI) in aiding clinical decision-making and management of stroke and heart diseases have become increasingly common in recent years, thanks in part to technological advancements and the heightened interest ...

Using Health Chatbots for Behavior Change: A Mapping Study.

Journal of medical systems
This study conducts a mapping study to survey the landscape of health chatbots along three research questions: What illnesses are chatbots tackling? What patient competences are chatbots aimed at? Which chatbot technical enablers are of most interest...

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...

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...

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...