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<p class="MsoNormal">Interesting webinar related to machine learning and prevention science -- details below!<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal"><b><span style="font-size:12.0pt;color:black">From: </span></b><span style="font-size:12.0pt;color:black">The NIH Office of Disease Prevention <prevention@mail.nih.gov><br>
<b>Reply-To: </b>"prevention@mail.nih.gov" <prevention@mail.nih.gov><br>
<b>Date: </b>Wednesday, August 16, 2017 at 8:43 AM<br>
<b>To: </b>Leslie Leve <leve@uoregon.edu><br>
<b>Subject: </b>Upcoming NIH Webinar: Automating Machine Learning for Prevention Research<o:p></o:p></span></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal"><img width="1" height="1" id="_x0000_i1025" src="http://r20.rs6.net/on.jsp?a=1102776244791&r=3&c=212b7ae0-92f4-11e3-ba91-d4ae52733bf0&d=1128618444291&ch=16c59a00-9c12-11e3-8283-d4ae52754055&ca=7e93908c-a15d-4bce-b544-9ba7883d3144&o=https://imgssl.constantcontact.com/ui/images1/s.gif"><o:p></o:p></p>
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<p class="MsoNormal" align="center" style="text-align:center"><a href="http://r20.rs6.net/tn.jsp?f=001RLxywyIAUoMFN_ZxhnPRxv2VmlEFoxu0ipCaodaGQtJhde6MJmIrBBmZwMJEPQVrt9uGIhl9bM9nkGF3c7xAkWZt53qiK2yc28UD84aFvbCjQnSV2SjazhXGyBc7S3yxrhuy_dV2xZXuKfJoQJWRAoomHQWCeX3tydVQWREkeH3_MOFaWnA5-tTpNbHgt0MxegBZnKrE1LTFLfY6V9LAu6k2yOQem0lCUXEuqK5Bu78PS4GmM243OoVUBE6Oqijt_fIhFRx9uFFf66jZjxBOTg==&c=9I4GWD21cL-OFDZ0RNhhh07UpLwTtrQP7YWAyGK3APCkGgXYwXjVXQ==&ch=eR2dnTak1pY36AyuhOU1K7EHa9EOnVuf86DjPYh9Tvlk81hVrPL__Q==" target="_blank"><span style="text-decoration:none"><img border="0" width="605" height="108" id="_x0000_i1026" src="https://mlsvc01-prod.s3.amazonaws.com/73a1692c001/391f8297-2bf9-405a-b940-7cafe5357d9c.png?ver=1488391357000" alt="edicine: Mind the Gap; NIH Seminar Series"></span></a><o:p></o:p></p>
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<h2 align="center" style="text-align:center;line-height:16.8pt;mso-line-height-rule:exactly">
<span style="font-size:15.0pt;color:white">Automating Machine Learning for Prevention Research<o:p></o:p></span></h2>
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<span style="font-size:10.5pt;font-family:"Helvetica",sans-serif;color:white">Presented by<o:p></o:p></span></p>
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<strong><span style="font-size:12.0pt;font-family:"Helvetica",sans-serif;color:white">Jason Moore, Ph.D.</span></strong><span style="font-size:12.0pt;font-family:"Helvetica",sans-serif;color:white"><o:p></o:p></span></p>
<p align="center" style="text-align:center;line-height:15.6pt;mso-line-height-rule:exactly;-ms-text-size-adjust: 100%;-webkit-text-size-adjust: 100%">
<span style="font-size:10.5pt;font-family:"Helvetica",sans-serif;color:white">Director, Institute for Biomedical Informatics<br>
Perelman School of Medicine, University of Pennsylvania<o:p></o:p></span></p>
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<strong><span style="font-size:12.0pt;font-family:"Helvetica",sans-serif;color:white">Tuesday, August 29, 2017 | 11:00 a.m. to 12:00 noon ET</span></strong><span style="font-size:12.0pt;font-family:"Helvetica",sans-serif;color:white"><o:p></o:p></span></p>
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<strong><span style="font-size:10.5pt;font-family:"Helvetica",sans-serif;color:#515151">Sponsored by the
<a href="http://r20.rs6.net/tn.jsp?f=001RLxywyIAUoMFN_ZxhnPRxv2VmlEFoxu0ipCaodaGQtJhde6MJmIrBJxCliT6zWFQ2zgViO21OJOwxaVMa99pCmpw4_mutmZa0uWpY4Xrwa5InaZ2o9iCPhJ3CDAMonAJ6QKDttybMhrpYkE7hj1HrOL_-Lf2Ko48Hvp9NY4P6bxYuo_E82ydsAc15nzeJMm72pYhErZmIlKddY5JSaJaSU6CMfzvgsTLBm-StjJ-QWj55TTjvwnNCQ==&c=9I4GWD21cL-OFDZ0RNhhh07UpLwTtrQP7YWAyGK3APCkGgXYwXjVXQ==&ch=eR2dnTak1pY36AyuhOU1K7EHa9EOnVuf86DjPYh9Tvlk81hVrPL__Q==">
<span style="color:#1A0DAB;font-weight:normal">NIH Office of Disease Prevention</span></a>.</span></strong><span style="font-size:10.5pt;font-family:"Helvetica",sans-serif;color:#515151"><o:p></o:p></span></p>
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<span style="font-size:10.5pt;font-family:"Helvetica",sans-serif;color:#515151">Successful disease prevention will depend on modeling human health as a complex system that is dynamic in time and space and driven by biomolecular and physiologic interactions.
 Machine learning holds promise for embracing this complexity in Big Data. Unfortunately, the barrier to machine learning is steep, requiring knowledge about many different types of algorithms and methods that need to be combined in an analytical pipeline.
 Dr. Moore will discuss this new discipline of automated machine learning (AutoML) that has the goal of simplifying this process and making machine learning more accessible.
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 Mind the Gap</span></a> is a webinar series that explores research design, measurement, intervention, data analysis, and other methods of interest to prevention science.<o:p></o:p></span></p>
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<strong><span style="font-size:10.5pt;font-family:"Helvetica",sans-serif;color:#515151">Dr. Moore will accept questions during the webinar via WebEx and on Twitter with #NIHMtG.</span></strong><span style="font-size:10.5pt;font-family:"Helvetica",sans-serif;color:#515151">
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<span style="font-size:10.5pt;font-family:"Helvetica",sans-serif;color:#515151">For more information, please contact the Office of Disease Prevention at
<a href="mailto:prevention@mail.nih.gov"><span style="color:#1A0DAB">prevention@mail.nih.gov</span></a>.<o:p></o:p></span></p>
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<span style="font-size:7.5pt;font-family:"Helvetica",sans-serif;color:#515151">Division of Program Coordination, Planning, and Strategic Initiatives (DPCPSI)<o:p></o:p></span></p>
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