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Shihan Wang

Datos Biográficos

ID7679953
NOMBREShihan Wang
NOMBRESShihan
APELLIDOWang
FIRMAWANG S
AFILIACIONESUtrecht University
ORCID0000-0001-6854-9217
VERIFICADOSí
TOTAL DE OBRAS6
TOTAL DE CITAS0
TOTAL COMO AUTOR6
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2021
AÑO MÁS RECIENTE DE PUBLICACIÓN2025
ÍNDICE H0
  • The epidemiology and burden of atherosclerotic cardiovascular disease in China from 1990 to 2021

    Open Access•Xin-Zheng Hou, Qian Wu et al.•ARTICLE•Frontiers in Public Health•2025

    Background: Atherosclerotic cardiovascular disease (ASCVD) significantly threatens the health of the Chinese population. Understanding its epidemiological burden is vital for targeted interventions. Methods: Using Global Burden of Diseases (GBD) 2021 data, we assessed Disability-Adjusted Life Years (DALYs), incidence, prevalence, and mortality of ischemic heart disease (IHD), stroke, and lower extremity peripheral artery disease (PAD) in China in…

  • Childhood obesity inequality in northeast China

    Open Access•Yang Liu, Angela C B Trude et al.•ARTICLE•BMC Public Health•2023

    Girls from moderate wealth & self-employed families may be the group susceptible to school neighborhood environment. Local policies targeted at improving the school neighborhood environment may be one avenue for reducing socioeconomic disparities in obesity especially for girls

  • Spatiotemporal variations of public opinion on social distancing in the Netherlands

    Open Access•Chao Zhang, Shihan Wang et al.•ARTICLE•Frontiers in Public Health•2022

    Background: Social distancing has been implemented by many countries to curb the COVID-19 pandemic. Understanding public support for this policy calls for effective and efficient methods of monitoring public opinion on social distancing. Twitter analysis has been suggested as a cheaper and faster-responding alternative to traditional survey methods. The current empirical evidence is mixed in terms of the correspondence between the two methods. Ob…

  • What Are Good Situations for Running? A Machine Learning Study Using Mobile and Geographical Data

    Open Access•Shihan Wang, Simon Scheider et al.•ARTICLE•Frontiers in Public Health•2021

    Running is a popular form of physical activity. Personal, social, and environmental determinants influence the engagement of the individual. To get insight in the relation between running behavior and external situations for different types of users, we carried out an extensive data mining study on large-scale datasets. We combined 4 years of historical running data (collected by a mobile exercise application from over 10K participants) with weat…

  • The Design and Development of a Personalized Leisure Time Physical Activity Application Based on Behavior Change Theories, End-User Perceptions, and Principles From Empirical Data Mining

    Open Access•Karlijn Sporrel, R De Boer et al.•ARTICLE•Frontiers in Public Health•2021

    Introduction: Many adults do not reach the recommended physical activity (PA) guidelines, which can lead to serious health problems. A promising method to increase PA is the use of smartphone PA applications. However, despite the development and evaluation of multiple PA apps, it remains unclear how to develop and design engaging and effective PA apps. Furthermore, little is known on ways to harness the potential of artificial intelligence for de…

  • Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application

    Open Access•Shihan Wang, Karlijn Sporrel et al.•ARTICLE•International Journal of…•2021

    Just-in-time adaptive intervention (JITAI) has gained attention recently and previous studies have indicated that it is an effective strategy in the field of mobile healthcare intervention. Identifying the right moment for the intervention is a crucial component. In this paper the reinforcement learning (RL) technique has been used in a smartphone exercise application to promote physical activity. This RL model determines the 'right' time to deli…

Sin obras prominentes en esta página.

  • What Are Good Situations for Running? A Machine Learning Study Using Mobile and Geographical Data

    Open Access•Shihan Wang, Simon Scheider et al.•ARTICLE•Frontiers in Public Health•2021

    Running is a popular form of physical activity. Personal, social, and environmental determinants influence the engagement of the individual. To get insight in the relation between running behavior and external situations for different types of users, we carried out an extensive data mining study on large-scale datasets. We combined 4 years of historical running data (collected by a mobile exercise application from over 10K participants) with weat…

  • The Design and Development of a Personalized Leisure Time Physical Activity Application Based on Behavior Change Theories, End-User Perceptions, and Principles From Empirical Data Mining

    Open Access•Karlijn Sporrel, R De Boer et al.•ARTICLE•Frontiers in Public Health•2021

    Introduction: Many adults do not reach the recommended physical activity (PA) guidelines, which can lead to serious health problems. A promising method to increase PA is the use of smartphone PA applications. However, despite the development and evaluation of multiple PA apps, it remains unclear how to develop and design engaging and effective PA apps. Furthermore, little is known on ways to harness the potential of artificial intelligence for de…

  • Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application

    Open Access•Shihan Wang, Karlijn Sporrel et al.•ARTICLE•International Journal of…•2021

    Just-in-time adaptive intervention (JITAI) has gained attention recently and previous studies have indicated that it is an effective strategy in the field of mobile healthcare intervention. Identifying the right moment for the intervention is a crucial component. In this paper the reinforcement learning (RL) technique has been used in a smartphone exercise application to promote physical activity. This RL model determines the 'right' time to deli…

  • Spatiotemporal variations of public opinion on social distancing in the Netherlands

    Open Access•Chao Zhang, Shihan Wang et al.•ARTICLE•Frontiers in Public Health•2022

    Background: Social distancing has been implemented by many countries to curb the COVID-19 pandemic. Understanding public support for this policy calls for effective and efficient methods of monitoring public opinion on social distancing. Twitter analysis has been suggested as a cheaper and faster-responding alternative to traditional survey methods. The current empirical evidence is mixed in terms of the correspondence between the two methods. Ob…

  • Childhood obesity inequality in northeast China

    Open Access•Yang Liu, Angela C B Trude et al.•ARTICLE•BMC Public Health•2023

    Girls from moderate wealth & self-employed families may be the group susceptible to school neighborhood environment. Local policies targeted at improving the school neighborhood environment may be one avenue for reducing socioeconomic disparities in obesity especially for girls

  • The epidemiology and burden of atherosclerotic cardiovascular disease in China from 1990 to 2021

    Open Access•Xin-Zheng Hou, Qian Wu et al.•ARTICLE•Frontiers in Public Health•2025

    Background: Atherosclerotic cardiovascular disease (ASCVD) significantly threatens the health of the Chinese population. Understanding its epidemiological burden is vital for targeted interventions. Methods: Using Global Burden of Diseases (GBD) 2021 data, we assessed Disability-Adjusted Life Years (DALYs), incidence, prevalence, and mortality of ischemic heart disease (IHD), stroke, and lower extremity peripheral artery disease (PAD) in China in…

Computer Science (4 obras) · Psychology (4 obras) · Medicine (3 obras) · Population (3 obras) · Artificial Intelligence (2 obras) · Environmental health (2 obras) · Epidemiology (2 obras) · Geography (2 obras) · Human–computer interaction (2 obras) · Mobile Health and mHealth Applications (2 obras)

Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae