Article

Impacts of batch effects on the performance of machine learning classifiers across multiple studies

2026-06-30

Abstract excerpt

Precision medicine relies on accurate and generalizable predictions for patients across the spectrum of human diversity. Because capturing biological heterogeneity requires large sample sizes, researchers must often aggregate data from several experimental batches or independent studies. This integration allows for greater statistical power and diversity than a single study could provide, while avoiding the costs...

Topics

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

Identifiers and source

Literature Corpus work: e99250d5-c1a5-5309-ada5-3fdc852af661
DOI: 10.64898/2026.06.24.734352

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Impacts of batch effects on the performance of machine learning classifiers across multiple studiesDOI 10.64898/2026.06.24.734352Read

BatchVaria: a variance-aware framework for evaluating batch correction in high-dimensional omics dataSemantic proximity Read

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

Robustifying genomic classifiers to batch effects via ensemble learningSemantic proximity Read

Batch Normalization Followed by Merging Is Powerful for Phenotype Prediction Integrating Multiple Heterogeneous StudiesSemantic proximity Read

Measuring the effect of inter-study variability on estimating prediction error.Semantic proximity Read

Deep learning based multi-batch calibration for classification in various omicsSemantic proximity Read

The impact of different sources of heterogeneity on loss of accuracy from genomic prediction modelsSemantic proximity Read

Paired-Sample and Pathway-Anchored MLOps Framework for Robust Transcriptomic Machine Learning in Small CohortsSemantic proximity Read

Empowering Multi-Cohort Gene Expression Analysis to Increase ReproducibilitySemantic proximity Read

PALMO: a comprehensive platform for analyzing longitudinal multi-omics dataSemantic proximity Read

NPmatch: Latent Batch Effects Correction of Omics data by Nearest-Pair MatchingSemantic proximity Read

Recommendations for Validating Omics Prediction Models: Insights from a Lung Cancer RNA Biomarker StudySemantic proximity Read