Article

Domain-Invariant Feature Learning for Patient-Level Phenotype Prediction from Single-Cell Data

2025-09-25

Abstract excerpt

Accurate prediction of patient-level disease status from single-cell RNA sequencing (scRNA-seq) data is critical to enabling precision diagnostics. However, study-specific artifacts induce spurious correlations that limit generalization and interpretability. We studied this problem in the context of Multiple Instance Learning (MIL), a framework where each patient is modeled as a set of single-cell profiles. To imp...

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Literature Corpus work: 51f8e334-ae22-50b0-acf8-576d783cb809
DOI: 10.1101/2025.09.22.677881

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