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Using big data searching and machine learning to predict human health risk probability from pesticide site soils in

Xin Wang1, Dongsheng Yu1, Lixia Ma2

  • 1State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China; University of Chinese Academy of Sciences, Beijing 100049, China.

Journal of Environmental Management
|August 6, 2022
PubMed
Abstract

No abstract available in PubMed .

Keywords:
Human health riskLabel propagation algorithmPesticide siteRisk probability predictionSemi-supervised learning model

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In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
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