An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records
无监督从电子健康病例预测患者未来的健康 摘要 电子健康记录（EHR）的二次使用有望推动临床研究的发展和改善告知临床决策。汇总和表示患者数据方面的挑战阻止了使用EHR进行预测建模的广泛实践。在这里，我们介绍了一种新颖的无监督的特征学习方法从EHR数据得出通用的患者代表促进临床预测建模。特别是三层去噪自动编码器堆栈用于捕获约EHRs的汇总EHR中的分层规则和依存关系来自西奈山数据仓库的700,000名
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相关文章
- 1. 【论文阅读笔记】Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Elec
- 2. The Future of AI in the Era of IoT
- 3. read the python code and predict the results --- from
- 4. Electronic Edition of the Book《Elon Musk》
- 5. The Future of Compass & ElasticSearch
- 6. The future of microprocessors
- 7. Why is the cooling of electronic devices so important?
- 8. An association from the table content refers to an
- 9. How Big Data has the Potential to Save Lives
- 10. On the use of machine learning to predict the time and resources consumed by applications