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New benchmarks improve IBD classification using donor-aware scRNA-seq analysis

Researchers have developed a donor-aware benchmark for classifying Inflammatory Bowel Disease (IBD) using single-cell RNA sequencing (scRNA-seq) data. This new benchmark addresses the issue of pseudoreplication by ensuring that training and testing data come from different donors. The study evaluated three feature representations, including centered log-ratio (CLR) transformed cell-type composition and GatedStructuralCFN dependency embeddings, across two independent IBD cohorts. AI

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IMPACT Introduces a more rigorous evaluation framework for biological data analysis, potentially improving the reliability of AI models in disease classification.

RANK_REASON The cluster contains an academic paper detailing a new benchmark and evaluation methodology for biological data analysis.

Read on arXiv cs.LG →

COVERAGE [2]

  1. arXiv cs.LG TIER_1 · Jonathan Muhire ·

    Donor-Aware scRNA-seq Benchmarks for IBD Classification

    arXiv:2605.03281v1 Announce Type: cross Abstract: Donor-level disease classification from single-cell RNA sequencing (scRNA-seq) requires strict donor-aware cross-validation: naive pipelines that split cells randomly conflate training and test donors, inflating reported performan…

  2. arXiv stat.ML TIER_1 · Jonathan Muhire ·

    Donor-Aware scRNA-seq Benchmarks for IBD Classification

    Donor-level disease classification from single-cell RNA sequencing (scRNA-seq) requires strict donor-aware cross-validation: naive pipelines that split cells randomly conflate training and test donors, inflating reported performance through pseudoreplication. We present a donor-a…