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About Medical Concept Normalization For Online User-Generated Texts
This paper proposes a novel approach for medical concept normalization of user-generated texts from social media. The approach uses deep learning models like CNNs and RNNs trained on various clinical domain-specific knowledge sources to map health conditions described in colloquial language to standardized medical concepts. Experiments on two benchmark datasets show the proposed models achieve up to 21.28% accuracy improvement over existing models when combining all knowledge sources to learn neural embeddings for concept normalization.
Detailed Information
| Author: | ['Suresh Shirasath'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 8 |
| Language: | English |
| Format: | |
| Price: | FREE |
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