David Rehkopf
6 SlideShares 1 Seguidor
Personal Information
Organización/Lugar de trabajo
San Francisco Bay Area United States
Ocupación
Assistant Professor at Stanford University
Sector
Education
Sitio web
http://med.stanford.edu/profiles/David_Rehkopf/
Datos de contacto
Etiquetas
heterogeneity machine learning population health epidemiology eitc stanford social determinants of health public health recursive partitioning random forest artificial intelligence health inequalities methylation dna social policy hte lasso longevity mortality demography aging biodemography telomere
Ver más

Presentaciones

(6)
Ver todo

Adversity, Poverty and Stress over the Life course: Consequences for human biology and development

Hace 7 años • 323 Visualizaciones

Telomere Length as a Predictor for Longevity and Specific Mortality

Hace 7 años • 443 Visualizaciones

Heterogeneous impacts of the Earned Income Tax Credit (EITC)

Hace 6 años • 74 Visualizaciones

Using Machine Learning to Examine Heterogeneity of the Effects of Changes in the Earned Income Tax Credit on Child Health and Development

Hace 6 años • 129 Visualizaciones

An introduction to population based data for studies of DNA methylation

Hace 5 años • 383 Visualizaciones

19 lu_machine_learning_final

Hace 4 años • 180 Visualizaciones
Personal Information
Organización/Lugar de trabajo
San Francisco Bay Area United States
Ocupación
Assistant Professor at Stanford University
Sector
Education
Sitio web
http://med.stanford.edu/profiles/David_Rehkopf/
Etiquetas
heterogeneity machine learning population health epidemiology eitc stanford social determinants of health public health recursive partitioning random forest artificial intelligence health inequalities methylation dna social policy hte lasso longevity mortality demography aging biodemography telomere
Ver más