Method to Create Digital Twins and use the Same for Causal Associations

摘要

The technology disclosed relates to systems and methods for predicting digital twins. The system includes logic to use a machine learning model predict correlation between pairs of persons and save the results in an environmental and phenotypic correlation matrix. The inputs to the machine learning model can include data from individual-level and group-level datasets. The individual-level datasets include administration dataset including clinical data and person dataset including personal data. The group-level datasets include exposome dataset including environmental exposure and subpopulation dataset. The system includes logic to use the environmental and phenotypic correlation matrix as a random effect when determining associations between exposures and outcomes. The system includes a second machine learning model that can take a pair of exposure and outcome and the environmental and phenotypic correlation matrix as input to predict causal association between exposure and outcome.