Assessing the Impact of Infrastructure and Social Environment Predictors on Road Accidents in Switzerland Using Machine Learning Algorithms and Open Large-Scale Dataset
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Key Points
Machine learning algorithms accurately predict road accidents, enhancing public health strategies.
The random forest model showed superior performance with a specificity of 0.88 and a negative predictive value of 0.96.
Utilizing open-access datasets allows for the integration of environmental and socio-economic factors in predictions.
This approach emphasizes the need for continuous data collection and sharing to inform traffic management policy.
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Implication
Analysis reveals that machine learning models accurately predict road accidents, suggesting improvements for public health policy.