SimPrints: Difference between revisions
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(Created page with "Contacts: Dan Storisteanu <dan@simprints.com> Nicolas Moreno de Palma <nicolas@simprints.com> With: Jonathan Luke Heeney <jlh66@cam.ac.uk> suggestion ... Fever Finder Goog...") |
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Contacts: Dan Storisteanu <dan@simprints.com> Nicolas Moreno de Palma <nicolas@simprints.com> | Contacts: Dan Storisteanu <dan@simprints.com> Nicolas Moreno de Palma <nicolas@simprints.com> | ||
With: Jonathan | With: Jonathan Heeney <jlh66@cam.ac.uk> | ||
suggestion ... | suggestion ... | ||
Fever Finder | [[Fever Finder]] | ||
Google Flu Trends was a famous (but unsuccessful) attempt to predict flu outbreaks on the basis of anxious people searching for symptoms. A more pressing need is to work out whether people in remote villages might be harbouring an outbreak of Lassa, Zika or Ebola. Your goal is to design a smartphone-based field station that geolocates fever symptoms for members of a family or village, using technology from Cambridge startup SimPrints to identify individual cases. With advice from an infectious disease specialist, you can use machine learning to model potential outbreaks as they occur. | Google Flu Trends was a famous (but unsuccessful) attempt to predict flu outbreaks on the basis of anxious people searching for symptoms. A more pressing need is to work out whether people in remote villages might be harbouring an outbreak of Lassa, Zika or Ebola. Your goal is to design a smartphone-based field station that geolocates fever symptoms for members of a family or village, using technology from Cambridge startup SimPrints to identify individual cases. With advice from an infectious disease specialist, you can use machine learning to model potential outbreaks as they occur. | ||
Latest revision as of 07:22, 28 October 2018
Contacts: Dan Storisteanu <dan@simprints.com> Nicolas Moreno de Palma <nicolas@simprints.com>
With: Jonathan Heeney <jlh66@cam.ac.uk>
suggestion ...
Google Flu Trends was a famous (but unsuccessful) attempt to predict flu outbreaks on the basis of anxious people searching for symptoms. A more pressing need is to work out whether people in remote villages might be harbouring an outbreak of Lassa, Zika or Ebola. Your goal is to design a smartphone-based field station that geolocates fever symptoms for members of a family or village, using technology from Cambridge startup SimPrints to identify individual cases. With advice from an infectious disease specialist, you can use machine learning to model potential outbreaks as they occur.
