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About Towards Automated ICD Coding Using Deep Learning
This document summarizes a research paper that proposes a deep learning model to automatically assign International Classification of Diseases (ICD) diagnostic codes given written medical diagnosis descriptions. The model uses character-aware neural networks and attention mechanisms to learn representations of diagnoses and ICD codes despite their different styles of writing. Evaluation on over 11,000 patient records shows the model achieves an F1 score of 0.53 and area under the receiver operating characteristic curve of 0.90 for ICD coding, outperforming models without attention mechanisms or character awareness. The researchers believe this framework could help automate and improve the accuracy of ICD coding.
Detailed Information
| Author: | ['Summer Rogers'] |
|---|---|
| Publication Year: | 2018 |
| Pages: | 11 |
| Language: | English |
| Format: | |
| Price: | FREE |
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