Papers by Heejoon Koo

1 papers
Next Visit Diagnosis Prediction via Medical Code-Centric Multimodal Contrastive EHR Modelling with Hierarchical Regularisation (2024.findings-eacl)

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Challenge: Existing studies have not addressed the heterogeneous and hierarchical properties inherent in EHR data.
Approach: They propose a medical code-centric multimodal contrastive EHR learning framework with hierarchical regularisation that integrates multifaceted information encompassing medical codes, demographics, and clinical notes.
Outcome: The proposed framework integrates multifaceted information encompassing medical codes, demographics, and clinical notes using a tailored network design and bimodal contrastive losses.

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