Genomic and algorithm-based predictive risk assessment models for benzene exposure.

Journal: Frontiers in public health
PMID: 39911783

Abstract

AIM: In this research, we leveraged bioinformatics and machine learning to pinpoint key risk genes associated with occupational benzene exposure and to construct genomic and algorithm-based predictive risk assessment models.

Authors

  • Minyun Jiang
    School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
  • Na Cai
    School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
  • Juan Hu
    School of Public Health, Southeast University, Nanjing, Jiangsu, China.
  • Lei Han
    Jiangsu Province Center for Disease Prevention and Control, Institute of Occupational Disease Prevention, Nanjing, Jiangsu, China.
  • Fanwei Xu
    School of Public Health, Southeast University, Nanjing, Jiangsu, China.
  • Baoli Zhu
    School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China.
  • Boshen Wang
    Jiangsu Province Center for Disease Prevention and Control, Institute of Occupational Disease Prevention, Nanjing, Jiangsu, China.

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