Machine learning to refine decision making within a syndromic surveillance service
Abstract Background Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical alarms highlighting potential activity of pu...
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| Main Authors: | , , , , , |
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| Format: | Book |
| Published: |
BMC,
2019-05-01T00:00:00Z.
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| Subjects: | |
| Online Access: | Connect to this object online. |
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