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Rashida R Brown

Datos Biográficos

ID6071107
NOMBRERashida R Brown
NOMBRESRashida R
APELLIDOBrown
FIRMABROWN R R
AFILIACIONESIan Pan is with the Department of Biostatistics, School of Public Health, Brown University, Providence, RI. Laura B. Nolan is with the Population Research Center, School of Social Work, Columbia University, New York, NY. Rashida R. Brown is with the Division of Epidemiology, School of Public Health, University of California, Berkeley. Romana Khan is with the Kellogg School of Management, Northwestern University, Evanston, IL. Paul van der Boor and Rayid Ghani are with the Center for Data Science and...
VERIFICADONo
TOTAL DE OBRAS3
TOTAL DE CITAS4
TOTAL COMO AUTOR3
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2015
AÑO MÁS RECIENTE DE PUBLICACIÓN2021
ÍNDICE H2
  • Legacies of Environmental Injustice on Neighborhood Violence, Poverty and Active Living in an African American Community

    Erica Payton, Rashida R Brown et al.•ARTICLE•Ethnicity & Disease•2021

    Features of the built environment such as parks and open spaces contribute to increased physical activity in populations, while living in neighborhoods with high poverty, racial/ethnic segregation, presence of neighborhood problems, and violence has been associated with less active living. Our present study examined the factors that may facilitate or hinder the long-term success of built environment interventions aimed at promoting physical activ…

  • Machine Learning for Social Services

    Ian Pan, Laura B Nolan et al.•ARTICLE•American Journal of Public Health•2017•Citada por: 2•Referencias: 19

    Objectives. To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services. Methods. We used administrative data for 6457 women collected by the Illinois Department of Human Services from July 2014 to May 2015 to develop a machine learning model for adverse birth prediction and improve upon the existing paper-based r…

  • Acute responses to opioidergic blockade as a biomarker of hedonic eating among obese women enrolled in a mindfulness-based weight loss intervention trial

    Open Access•Ashley E Mason, Robert H Lustig et al.•ARTICLE•Appetite•2015•Citada por: 2•Referencias: 60

  • Machine Learning for Social Services

    Ian Pan, Laura B Nolan et al.•ARTICLE•American Journal of Public Health•2017•Citada por: 2•Referencias: 19

    Objectives. To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services. Methods. We used administrative data for 6457 women collected by the Illinois Department of Human Services from July 2014 to May 2015 to develop a machine learning model for adverse birth prediction and improve upon the existing paper-based r…

  • Acute responses to opioidergic blockade as a biomarker of hedonic eating among obese women enrolled in a mindfulness-based weight loss intervention trial

    Open Access•Ashley E Mason, Robert H Lustig et al.•ARTICLE•Appetite•2015•Citada por: 2•Referencias: 60

  • Acute responses to opioidergic blockade as a biomarker of hedonic eating among obese women enrolled in a mindfulness-based weight loss intervention trial

    Open Access•Ashley E Mason, Robert H Lustig et al.•ARTICLE•Appetite•2015•Citada por: 2•Referencias: 60

  • Machine Learning for Social Services

    Ian Pan, Laura B Nolan et al.•ARTICLE•American Journal of Public Health•2017•Citada por: 2•Referencias: 19

    Objectives. To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services. Methods. We used administrative data for 6457 women collected by the Illinois Department of Human Services from July 2014 to May 2015 to develop a machine learning model for adverse birth prediction and improve upon the existing paper-based r…

  • Legacies of Environmental Injustice on Neighborhood Violence, Poverty and Active Living in an African American Community

    Erica Payton, Rashida R Brown et al.•ARTICLE•Ethnicity & Disease•2021

    Features of the built environment such as parks and open spaces contribute to increased physical activity in populations, while living in neighborhoods with high poverty, racial/ethnic segregation, presence of neighborhood problems, and violence has been associated with less active living. Our present study examined the factors that may facilitate or hinder the long-term success of built environment interventions aimed at promoting physical activ…

Medicine (3 obras) · Psychological intervention (2 obras) · Psychology (2 obras) · Active living (1 obras) · Addiction (1 obras) · Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (1 obras) · Artificial Intelligence (1 obras) · Artificial Intelligence (1 obras) · Binge eating (1 obras) · Built environment (1 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