Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records.
<h4>Background</h4>Emergency admissions are a major source of healthcare spending. We aimed to derive, validate, and compare conventional and machine learning models for prediction of the first emergency admission. Machine learning methods are capable of capturing complex interactions th...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2018-11-01
|
| Series: | PLoS Medicine |
| Online Access: | https://doi.org/10.1371/journal.pmed.1002695 |