Google Flu Trends revisited: Improving influenza modelling from search query logs
i-sense work with Google Flu Trends to develop their modelling techniques and support a more accurate picture of flu rates in the UK.
i-sense work with Google Flu Trends to develop their modelling techniques and support a more accurate picture of flu rates in the UK.
i-sense work with Google Flu Trends to develop their modelling techniques and support a more accurate picture of flu in the UK.
i-sense, UCL and Microsoft researchers give tutorial on "Learning about health and medicine from Internet data" at WSDM 2015.
Researchers from Microsoft, UCL and i-sense have developed algorithms that can alert to possible outbreaks of infectious diseases at mass gatherings using internet data, specifically Twitter and search engine queries, as part of a study published in the Journal of Medical Internet Research.
Pandemic influenza is rated amongst the gravest national risks on the UK government risk register. Pandemics can occur with unpredictable frequency, infecting populations with a new virus over a relatively short period of time, causing significant illness and mortality and disrupting the function of normal communities. Early detection is key to preventing the spread of 'ordinary' seasonal and pandemic flu.
Flagship 3 aims to develop sensor systems to detect and identify bacterial pathogens, including Clostridium difficile, MRSA and VRE (Vancomycin Resistant Enterococci).
Mobile diagnostics will be developed for use in GP surgeries and care homes, taking advantage of new biomarker discovery tools to guide the development of a variety of capture molecules.
