Discovering patient groups in sequential electronic healthcare data using unsupervised representation learning
Abstract Introduction Unsupervised feature learning methods inspired by natural language processing (NLP) models are capable of constructing patient-specific features from longitudinal Electronic Health Records (EHR). Design We applied document embedding algorithms to real-world paediatric intensive...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-01-01
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| Series: | BMC Medical Informatics and Decision Making |
| Online Access: | https://doi.org/10.1186/s12911-024-02812-9 |
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