Records 1 - 5 (of 5 Records)
| Predicting Low-Level Childhood Lead Exposure in Metro Atlanta Using Ensemble Machine Learning of High-Resolution Raster Cells.
Seth Frndak et al. International journal of environmental research and public health 2023 20(5)
| A new approach to a legacy concern: Evaluating machine-learned Bayesian networks to predict childhood lead exposure risk from community water systems.
Mulhern Riley et al. Environmental research 2021 204(Pt B) 112146
| Novel Application of Machine Learning Algorithms and Model-Agnostic Methods to Identify Factors Influencing Childhood Blood Lead Levels.
Liu Xiaochi et al. Environmental science & technology 2021
| Validation of a Machine Learning Model to Predict Childhood Lead Poisoning.
Potash Eric et al. JAMA network open 2020 Sep 3(9) e2012734
| Association of lead-exposure risk and family income with childhood brain outcomes.
Marshall Andrew T et al. Nature medicine 2020 26(1) 91-97