Author

I. Konigsberg

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Open access Aug 2026

MT-LLE: Multi-task locally linear embedding for interpretable disease modeling from longitudinal omics data

Manifold learning is recast as multi-task learning: MT-LLE jointly optimizes five objectives: geometric reconstruction, supervised organization by clinical stage, embedding and phenotype forecasting, and clustering, which supports complementary analyses that surface structure invisible to standard staging.

S. Hussein, I. Konigsberg, K. Kechris et al. · bioRxiv · 0 citations

Review Open access Aug 2026

Practical considerations for social determinant-based disease prediction in the All of Us research program

It is shown that requiring sufficient individual-level SDoH survey data results in significant selection bias and sample reduction in AoU, and that area-level SDoH metrics contribute to disease prediction independently of individual-level measures.

M. Hysong, A. Manning, Michael D. Green et al. · Communications Health · 1 citation