Predicting neighborhood-level violence from features of the physical and social environment with machine learning.

ABSTRACT:

Background

Violence is a leading cause of death and disparity in the United States. Individuals' physical and social environments can prevent or foster violence, but these complex milieus are challenging to model. In this study, we used machine learning to identify features of the local environment that are most predictive of violence in two Midwestern cities struggling with disinvestment and crime.

Methods

This was a serial cross-sectional study of census tracts in Cleveland, Ohio and Detroit, Michigan, 2011-2019. We took a machine learning approach-extreme gradient boosting-that enabled us to model 55 neighborhood features simultaneously and without making assumptions about their relationships or functional form. These features included building quality and type, public go

SUBMITTER: Pear VA 

PROVIDER: S-EPMC12604338 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature