Latent class distributional regression for the estimation of non-linear reference limits from contaminated data sources.

Tobias HeppJakob ZierkManfred RauhMarkus MetzlerAndreas Mayr

Published in: BMC bioinformatics (2020)

Latent class distributional regression models represent the first method to estimate indirect non-linear reference limits from a single model fit, but the general scope of applications can be extended to other scenarios with latent heterogeneity.

Keyphrases

drinking water
climate change
heavy metals
electronic health record
single cell
big data
machine learning
neural network
risk assessment
artificial intelligence