Back to search

Article

Using Conditional Generative Adversarial Networks to Boost the Performance of Machine Learning in Microbiome Datasets

2020-05-21

Abstract excerpt

The microbiome of the human body has been shown to have profound effects on physiological regulation and disease pathogenesis. However, association analysis based on statistical modeling of microbiome data has continued to be a challenge due to inherent noise, complexity of the data, and high cost of collecting large number of samples. To address this challenge, we employed a deep learning framework to construct a...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
9c441573-a3a7-5825-bc04-f0ed5883aa8c
DOI
10.1101/2020.05.18.102814
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Using Conditional Generative Adversarial Networks to Boost the Performance of Machine Learning in Microbiome DatasetsDOI 10.1101/2020.05.18.102814
Select a neighboring publication to make it the new centre.