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Rashida R Brown

Biographic Data

ID6071107
NAMERashida R Brown
GIVEN NAMESRashida R
FAMILY NAMEBrown
SIGNATUREBROWN R R
AFFILIATIONSIan 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...
VERIFIEDNo
TOTAL WORKS3
TOTAL CITATIONS4
AUTHOR COUNT3
EDITOR COUNT0
FIRST PUBLICATION YEAR2015
LATEST PUBLICATION YEAR2021
H-INDEX2
  • 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•Cited by: 2•References: 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•Cited by: 2•References: 60

  • Machine Learning for Social Services

    Ian Pan, Laura B Nolan et al.•ARTICLE•American Journal of Public Health•2017•Cited by: 2•References: 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•Cited by: 2•References: 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•Cited by: 2•References: 60

  • Machine Learning for Social Services

    Ian Pan, Laura B Nolan et al.•ARTICLE•American Journal of Public Health•2017•Cited by: 2•References: 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 works) · Psychological intervention (2 works) · Psychology (2 works) · Active living (1 works) · Addiction (1 works) · Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (1 works) · Artificial Intelligence (1 works) · Artificial Intelligence (1 works) · Binge eating (1 works) · Built environment (1 works)

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