Disease trajectory embeddings from longitudinal EHR data serve as structural priors to enhance multi-organ IDP representation learning, improving AUC and MAE for disease prediction across 159 conditions in UK Biobank.
Nature 647, 248-256 (2025)
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DT-Transformer predicts next disease events with median age- and sex-stratified AUC 0.871 across 896 categories on held-out and prospective data from a 1.7M-patient multi-hospital EHR dataset.
The paper introduces ClinQueryAgent, a conversational agent that converts natural language queries into database queries for population health management while keeping patient data secure, and reports its use by 128 staff across 15 NHS practices covering 148,319 patients.
citing papers explorer
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From Trajectories to Phenotypes: Disease Progression as Structural Priors for Multi-organ Imaging Representation Learning
Disease trajectory embeddings from longitudinal EHR data serve as structural priors to enhance multi-organ IDP representation learning, improving AUC and MAE for disease prediction across 159 conditions in UK Biobank.
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DT-Transformer: A Foundation Model for Disease Trajectory Prediction on a Real-world Health System
DT-Transformer predicts next disease events with median age- and sex-stratified AUC 0.871 across 896 categories on held-out and prospective data from a 1.7M-patient multi-hospital EHR dataset.
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ClinQueryAgent: A Conversational Agent for Population Health Management
The paper introduces ClinQueryAgent, a conversational agent that converts natural language queries into database queries for population health management while keeping patient data secure, and reports its use by 128 staff across 15 NHS practices covering 148,319 patients.