3 papers
cs.AI2026
The Patient is not a Moving Document: A World Model Training Paradigm for Longitudinal EHR
Irsyad Adam, Zekai Chen, David Laprade +5
Large language models (LLMs) trained with next-word-prediction have achieved success as clinical foundation models. Representations from these language backbones yield strong linea…
q-bio.GN2025
GenVarFormer: Predicting gene expression from long-range mutations in cancer
David Laub, Ethan Armand, Arda Pekis +6
Distinguishing the rare "driver" mutations that fuel cancer progression from the vast background of "passenger" mutations in the non-coding genome is a fundamental challenge in can…
q-bio.QM2025
Patient-specific Biomolecular Instruction Tuning
Irsyad Adam, Zekai Chen, David Laub +3
Proteomics data is essential to pathogenic understanding of a disease phenotype. In cancer, analysis of molecular signatures enables precision medicine through the identification o…