AIMC Topic: Health Behavior
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Worker Perspectives on Incorporating Artificial Intelligence into Office Workspaces: Implications for the Future of Office Work.
International journal of environmental research and public health
Feb 10, 2021
Workplace environments have a significant impact on worker performance, health, and well-being. With machine learning capabilities, artificial intelligence (AI) can be developed to automate individualized adjustments to work environments (e.g., light...
PsychoAge and SubjAge: development of deep markers of psychological and subjective age using artificial intelligence.
Aging
Dec 8, 2020
Aging clocks that accurately predict human age based on various biodata types are among the most important recent advances in biogerontology. Since 2016 multiple deep learning solutions have been created to interpret facial photos, omics data, and cl...
Tree-Based Machine Learning to Identify and Understand Major Determinants for Stroke at the Neighborhood Level.
Journal of the American Heart Association
Nov 3, 2020
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
Oct 19, 2020
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
Jul 29, 2019
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 ...
Emergence of digital biomarkers to predict and modify treatment efficacy: machine learning study.
BMJ open
Jul 23, 2019
OBJECTIVES: Development of digital biomarkers to predict treatment response to a digital behavioural intervention.
Using Health Chatbots for Behavior Change: A Mapping Study.
Journal of medical systems
Apr 4, 2019
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
Jul 25, 2018
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
Jul 25, 2018
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
Mar 20, 2018
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...
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