{"version":"1.0","provider_name":"University Post","provider_url":"https:\/\/uniavisen.dk\/en\/","author_name":"University Post","author_url":"https:\/\/uniavisen.dk\/en\/","title":"DIKU Bits: Transfer learning to estimate influenza prevalence","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"n0kQfAP4dT\"><a href=\"https:\/\/uniavisen.dk\/en\/event\/diku-bits-transfer-learning-to-estimate-influenza-prevalence\/\">DIKU Bits: Transfer learning to estimate influenza prevalence<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/uniavisen.dk\/en\/event\/diku-bits-transfer-learning-to-estimate-influenza-prevalence\/embed\/#?secret=n0kQfAP4dT\" width=\"600\" height=\"338\" title=\"&#8220;DIKU Bits: Transfer learning to estimate influenza prevalence&#8221; &#8212; University Post\" data-secret=\"n0kQfAP4dT\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/uniavisen.dk\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","thumbnail_url":"https:\/\/uniavisen.dk\/wp-content\/uploads\/2019\/04\/img2656w235.png","thumbnail_width":235,"thumbnail_height":226,"description":"Speaker Ingemar J. Cox, professor in the Machine Learning Section at DIKU. Abstract It is now well-known that web searches can be\u00a0used to estimate the prevalence of influenza (and other diseases) in a\u00a0population. It is often claimed that\u00a0this approach is especially useful in low\u00a0and middle income countries (LMIC) where traditional health surveillance\u00a0infrastructures are poor or [&hellip;]"}