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arXiv · 1910.02574

Representation Learning of EHR Data via Graph-Based Medical Entity Embedding

Tong Wu·Yunlong Wang·Yue Wang·Emily Zhao·Yilian Yuan·Zhi Yang
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Abstract

Automatic representation learning of key entities in electronic health record (EHR) data is a critical step for healthcare informatics that turns heterogeneous medical records into structured and actionable information. Here we propose ME2Vec, an algorithmic framework for learning low-dimensional vectors of the most common entities in EHR: medical services, doctors, and patients. ME2Vec leverages diverse graph embedding techniques to cater for the unique characteristic of each medical entity. Using real-world clinical data, we demonstrate the efficacy of ME2Vec over competitive baselines on disease diagnosis prediction.

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Tong Wu, Yunlong Wang, Yue Wang, Emily Zhao, Yilian Yuan, Zhi Yang. 2019-10-07. Representation Learning of EHR Data via Graph-Based Medical Entity Embedding. https://arxiv.org/abs/1910.02574

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