Search Results for author: Vasileios Lampos

Found 9 papers, 1 papers with code

Estimating the Uncertainty of Neural Network Forecasts for Influenza Prevalence Using Web Search Activity

no code implementations26 May 2021 Michael Morris, Peter Hayes, Ingemar J. Cox, Vasileios Lampos

In this paper, we demonstrate how Bayesian Neural Networks (BNNs) can be used to both provide a forecast and a corresponding uncertainty without significant loss in forecasting accuracy compared to traditional NNs.

14 Decision Making

Providing early indication of regional anomalies in COVID19 case counts in England using search engine queries

no code implementations23 Jul 2020 Elad Yom-Tov, Vasileios Lampos, Ingemar J. Cox, Michael Edelstein

Our analysis shows that searches for "fever" and "cough" were the most correlated with future case counts, with searches preceding case counts by 16-17 days.

Tracking COVID-19 using online search

1 code implementation arXiv 2020 Vasileios Lampos, Simon Moura, Elad Yom-Tov, Michael Edelstein, Maimuna Majumder, Yohhei Hamada, Molebogeng X. Rangaka, Rachel A. McKendry, Ingemar J. Cox

Furthermore, we analyse the time series of online search queries in relation to confirmed COVID-19 cases data jointly across multiple countries, uncovering interesting patterns.

Social and Information Networks

Flu Detector: Estimating influenza-like illness rates from online user-generated content

no code implementations11 Dec 2016 Vasileios Lampos

We provide a brief technical description of an online platform for disease monitoring, titled as the Flu Detector (fludetector. cs. ucl. ac. uk).

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