A Masked Language Model for Multi-Source EHR Trajectories Contextual Representation Learning...33rd Medical Informatics Europe Conference (MIE2023), May 22-25, 2023, Gothenburg, Sweden.
Using electronic health records data and machine learning to guide future decisions needs to address challenges, including 1) long/short-term dependencies and 2) interactions between diseases and interventions. Bidirectional transformers have effectively addressed the first challenge. Here we tackle...
| Publicado en: | Studies in Health Technology & Informatics Vol. 302; pp. 609 - 611 |
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| Autores principales: | , , , , |
| Formato: | proceedings research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | Using electronic health records data and machine learning to guide future decisions needs to address challenges, including 1) long/short-term dependencies and 2) interactions between diseases and interventions. Bidirectional transformers have effectively addressed the first challenge. Here we tackled the latter challenge by masking one source (e.g., ICD10 codes) and training the transformer to predict it using other sources (e.g., ATC codes). |
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