AI RESEARCH
The Taxonomies, Training, and Applications of Event Stream Modelling for Electronic Health Records
arXiv CS.LG
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ArXi:2603.14003v1 Announce Type: cross The widespread adoption of electronic health records (EHRs) enables the acquisition of heterogeneous clinical data, spanning lab tests, vital signs, medications, and procedures, which offer transformative potential for artificial intelligence in healthcare. Although traditional modelling approaches have typically relied on multivariate time series, they often struggle to accommodate the inherent sparsity and irregularity of real-world clinical workflows.