Identifying and assessing the impact of key neighborhood-level determinants on geographic variation in stroke: a machine learning and multilevel modeling approach
Abstract Background Stroke is a chronic cardiovascular disease that puts major stresses on U.S. health and economy. The prevalence of stroke exhibits a strong geographical pattern at the state-level, where a cluster of southern states with a substantially higher prevalence of stroke has been called...
Saved in:
Main Authors: | Jiayi Ji (Author), Liangyuan Hu (Author), Bian Liu (Author), Yan Li (Author) |
---|---|
Format: | Book |
Published: |
BMC,
2020-11-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Sense of neighborhood belonging and health: geographic, racial, and socioeconomic variation in Wisconsin
by: Joseph A. Clark, et al.
Published: (2024) -
Multilevel analysis of geographic variation among correlates of child undernutrition in India
by: Anoop Jain, et al.
Published: (2021) -
Geographic variation and factors associated with anemia among under-fives in India: A multilevel approach
by: Jeetendra Yadav, et al.
Published: (2021) -
Geographical variation and associated factors of childhood measles vaccination in Ethiopia: a spatial and multilevel analysis
by: Tesfahun Taddege Geremew, et al.
Published: (2019) -
Combined docking and machine learning identify key molecular determinants of ligand pharmacological activity on β2 adrenoceptor
by: Mireia Jiménez‐Rosés, et al.
Published: (2022)