Back to search

Article

Batch Normalization Followed by Merging Is Powerful for Phenotype Prediction Integrating Multiple Heterogeneous Studies

2022-09-28

Abstract excerpt

Heterogeneity in different genomic studies compromises the performance of machine learning models in cross-study phenotype predictions. Overcoming heterogeneity when incorporating different studies in terms of phenotype prediction is a challenging and critical step for developing machine learning algorithms with reproducible prediction performance on independent datasets. We investigated the best approaches to int...

Topics

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

Identifiers and source

Literature Corpus work
adcb7888-973d-5d55-84ad-18b9b47c93b2
DOI
10.1101/2022.09.28.509843
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.
Batch Normalization Followed by Merging Is Powerful for Phenotype Prediction Integrating Multiple Heterogeneous StudiesDOI 10.1101/2022.09.28.509843
Select a neighboring publication to make it the new centre.