Batch normalization followed by merging is powerful for phenotype prediction integrating multiple heterogeneous studies.

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...

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