<html><head><meta http-equiv="Content-Type" content="text/html charset=iso-8859-1"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space; "><p class="">Please join us for the <b>NIPS 2014 Workshop on Machine Learning for Clinical Data, Healthcare and Genomics</b></p><p class=""><br></p><p class=""><span class="">When: </span><font color="#ff0000">Dec. 12th 2014, 8am-6:30pm</font></p><p class=""><span class="">Where: </span><span class=""> </span>Palais des congrès de Montréal, Level 5;<font color="#ff0000"> room 511 f.</font><span class="">, </span><span class="">Montreal, Quebec, Canada, </span></p><p class="">Workshop Website: <a href="http://www.ml4chg.org/">http://www.ml4chg.org/</a></p><p class=""><br></p><p class=""><u><b>Schedule:</b></u></p><table cellspacing="0" cellpadding="0" class=""><tbody><tr><td valign="middle" class=""><br class="webkit-block-placeholder"></td><td valign="middle" class=""><table cellspacing="0" cellpadding="0" class=""><tbody><tr><td valign="middle" class=""><p class="">Morning theme:</p></td><td valign="middle" class=""><p class="">Specialized models for structure recovery from clinical datasets</p></td></tr><tr><td valign="top" class=""><p class="">08:00-08:25 AM</p></td><td valign="top" class=""><p class="">Poster setup</p></td></tr><tr><td valign="top" class=""><p class="">08:25-08:35 AM</p></td><td valign="top" class=""><p class="">Introduction</p></td></tr><tr><td valign="top" class=""><p class="">08:35-09:30 AM</p></td><td valign="top" class=""><p class=""><span class=""><a href="https://dc8d3173c0293a531fbe6a6cdfc8f054fc0a2d46.googledrive.com/host/0B0TBaU3UgQ0DaF9hNlVYd2hUcFk/talk_1.html">Opening talk: John Mattison, Kaiser Permanente</a></span></p></td></tr><tr><td valign="top" class=""><p class="">09:30-10:00 AM</p></td><td valign="top" class=""><p class=""><span class=""><a href="https://dc8d3173c0293a531fbe6a6cdfc8f054fc0a2d46.googledrive.com/host/0B0TBaU3UgQ0DaF9hNlVYd2hUcFk/talk_2.html">Invited talk: David Sontag, New York University</a></span></p></td></tr><tr><td valign="top" class=""><p class="">10:00-10:30 AM</p></td><td valign="top" class=""><p class="">Coffee Break (and posters)</p></td></tr><tr><td valign="top" class=""><p class="">10:30-11:00 AM</p></td><td valign="top" class=""><p class="">Round table discussions</p></td></tr><tr><td valign="top" class=""><p class="">11:00-11:30 AM</p></td><td valign="top" class=""><p class=""><span class=""><a href="https://dc8d3173c0293a531fbe6a6cdfc8f054fc0a2d46.googledrive.com/host/0B0TBaU3UgQ0DaF9hNlVYd2hUcFk/talk_5.html">Invited talk: Gilles Clermont, University of Pittsburgh</a></span></p></td></tr><tr><td valign="top" class=""><p class="">11:30-12:00 PM</p></td><td valign="top" class=""><p class=""><span class=""><a href="https://dc8d3173c0293a531fbe6a6cdfc8f054fc0a2d46.googledrive.com/host/0B0TBaU3UgQ0DaF9hNlVYd2hUcFk/talk_6.html">Invited talk: Chris Williams, University of Edinburgh</a></span></p></td></tr><tr><td valign="top" class=""><p class="">12:00-03:00 PM</p></td><td valign="top" class=""><p class="">Lunch Break</p></td></tr><tr><td valign="middle" class=""><p class="">Afternoon theme:</p></td><td valign="middle" class=""><p class="">Clinical Genomics and Precision Medicine</p></td></tr><tr><td valign="top" class=""><p class="">3:00-3:30 PM</p></td><td valign="top" class=""><p class=""><span class=""><a href="https://dc8d3173c0293a531fbe6a6cdfc8f054fc0a2d46.googledrive.com/host/0B0TBaU3UgQ0DaF9hNlVYd2hUcFk/talk_3.html">Invited talk: Michal Rosen-Zvi, IBM Research</a></span></p></td></tr><tr><td valign="top" class=""><p class="">3:30-4:00 PM</p></td><td valign="top" class=""><p class=""><span class=""><a href="https://dc8d3173c0293a531fbe6a6cdfc8f054fc0a2d46.googledrive.com/host/0B0TBaU3UgQ0DaF9hNlVYd2hUcFk/talk_4.html">Invited talk: Michael Brudno, University of Toronto</a></span></p></td></tr><tr><td valign="top" class=""><p class="">4:00-4:30 PM</p></td><td valign="top" class=""><p class="">Poster Session</p></td></tr><tr><td valign="top" class=""><p class="">4:30-5:00 PM</p></td><td valign="top" class=""><p class="">Coffee Break (and posters)</p></td></tr><tr><td valign="top" class=""><p class="">5:00-5:30 PM</p></td><td valign="top" class=""><p class=""><span class=""><a href="https://dc8d3173c0293a531fbe6a6cdfc8f054fc0a2d46.googledrive.com/host/0B0TBaU3UgQ0DaF9hNlVYd2hUcFk/talk_7.html">Invited talk: Suchi Saria, Johns Hopkins University</a></span></p></td></tr><tr><td valign="top" class=""><p class="">5:30-6:30 PM</p></td><td valign="top" class=""><p class=""><span class=""><a href="http://paulfrohna.com/precision-vs-personalized-medicine-whats-the-difference/">Precision Medicine</a></span>: How to make it work? (Discussion Panel)</p></td></tr></tbody></table></td></tr></tbody></table><p class=""><u><b>Abstract:</b></u><br></p><p class="">Advances in medical information technology have resulted in enormous warehouses of data that are both overwhelming and sparse. A single patient visit may result in tens to thousands of measurements and structured information, including clinical factors, diagnostic imaging, lab tests, genomic and proteomic tests. Hospitals may see thousands of patients each year. However, each patient may have relatively few visits to any particular medical provider. The resulting data are a heterogeneous amalgam of patient demographics, vital signs, diagnoses, records of treatment and medication receipt and annotations made by nurses or doctors, each with its own idiosyncrasies.</p><p class="">The objective of this workshop is to discuss how advanced machine learning techniques can derive clinical and scientific impact from these messy, incomplete, and partial data. We will bring together machine learning researchers and experts in medical informatics who are involved in the development of algorithms or intelligent systems designed to improve quality of healthcare. Relevant areas include health monitoring systems, clinical data labelling and clustering, clinical outcome prediction, efficient and scalable processing of medical records, feature selection or dimensionality reduction in clinical data, tools for personalized medicine, time-series analysis with medical applications and clinical genomics.</p></body></html>