A sex difference-based mixed
pollutant key element
screening method belongs to the technical field of
environmental health monitoring and biological analysis, solves the technical problems of strong subjectivity, low precision and low efficiency of the existing
screening method, and comprises the following steps: S1, obtaining biological factor data; s2, acquiring in-vivo
pollutant element data; s3, regression model screening: screening out a regression model with the best performance in
pollutant key element screening; and S4, screening key elements. According to the method, a multi-dimensional fusion model is created by combining
X chromosome related genes, typical physiological indexes and
pollution element data in an
organism; on the basis, through an automatic model trained by
machine learning, manual intervention is reduced, the manpower and material resource cost is effectively reduced, the objectivity and efficiency of the screening process are improved, and according to the innovation, complex data are automatically processed through
data analysis, and the accuracy and consistency of operation are improved.