tetano
Editor, Senior Moderator
Sci Rep. 2016 May 11;6:25732. doi: 10.1038/srep25732.
[h=1]Cloud-based Electronic Health Records for Real-time, Region-specific Influenza Surveillance.[/h] Santillana M[SUP]1,[/SUP][SUP]2,[/SUP][SUP]3[/SUP], Nguyen AT[SUP]3[/SUP], Louie T[SUP]4[/SUP], Zink A[SUP]5[/SUP], Gray J[SUP]5[/SUP], Sung I[SUP]5[/SUP], Brownstein JS[SUP]1,[/SUP][SUP]2[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] Accurate real-time monitoring systems of influenza outbreaks help public health officials make informed decisions that may help save lives. We show that information extracted from cloud-based electronic health records databases, in combination with machine learning techniques and historical epidemiological information, have the potential to accurately and reliably provide near real-time regional estimates of flu outbreaks in the United States.
PMID: 27165494 [PubMed - in process]
[h=1]Cloud-based Electronic Health Records for Real-time, Region-specific Influenza Surveillance.[/h] Santillana M[SUP]1,[/SUP][SUP]2,[/SUP][SUP]3[/SUP], Nguyen AT[SUP]3[/SUP], Louie T[SUP]4[/SUP], Zink A[SUP]5[/SUP], Gray J[SUP]5[/SUP], Sung I[SUP]5[/SUP], Brownstein JS[SUP]1,[/SUP][SUP]2[/SUP].
[h=3]Author information[/h]
[h=3]Abstract[/h] Accurate real-time monitoring systems of influenza outbreaks help public health officials make informed decisions that may help save lives. We show that information extracted from cloud-based electronic health records databases, in combination with machine learning techniques and historical epidemiological information, have the potential to accurately and reliably provide near real-time regional estimates of flu outbreaks in the United States.
PMID: 27165494 [PubMed - in process]