Mixture density networks for the indirect estimation of reference intervals

Mixture density networks for the indirect estimation of reference intervals

Abstract Background Reference intervals represent the expected range of physiological test results in a healthy population and are essential to support medical decision making. Particularly in the context of pediatric reference intervals, where recruitment regulations make prospective studies challe...

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Bibliographic Details
Main Authors: Tobias Hepp, Jakob Zierk, Manfred Rauh, Markus Metzler, Sarem Seitz
Format: Article
Language:English
Published: BMC 2022-07-01
Series:BMC Bioinformatics
Subjects:
Mixture density networks
Reference intervals
Latent class regression
Distributional regression
Online Access:https://doi.org/10.1186/s12859-022-04846-0

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