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<!DOCTYPE html>
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<title>Joint KDD Health-Day and Applied Data Science for Healthcare</title>
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<a class="navbar-brand" href="#">KDD Health Day - DSHealth 2021</a>
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<li role="presentation" class="active"><a href="#home" aria-controls="home" role="tab" data-toggle="tab">Home</a></li>
<li role="presentation"><a href="#program" aria-controls="program" role="tab" data-toggle="tab">Program</a></li>
<li role="presentation"><a href="#papers" aria-controls="papers" role="tab" data-toggle="tab">Papers</a></li>
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<div class="jumbotron" id="about">
<h2>
Joint KDD 2021 Health Day and 2021 KDD Workshop on Applied Data Science for Healthcare
</h2>
<h4>State of XAI and trustworthiness in Health</h4>
<p style="padding-top:10px">
<span class="glyphicon glyphicon-globe"></span> Location: Join us virtually at <a href="https://virtual.2021.kdd.org/workshop_WS-36-B.html" target="_blank">KDD Virtual platform</a><br/>
<span class="glyphicon glyphicon-calendar"></span> Workshop Date: 2021, August 15, 11pm - Aug 16, 8am (<a href="https://savvytime.com/converter/sgt-to-cet-edt-pdt/aug-15-2021/11pm" target="_blank">SGT</a>)<br/>
<a href="https://twitter.com/HealthDs" target="_blank"><i class="fa fa-twitter"></i> Follow us on Twitter</a><br/>
</p>
</div>
</div>
<!--end jumbotron -->
<div class="container">
<div class="row">
<div class="tab-content">
<div role="tabpanel" class="tab-pane active" id="home"><br>
<div class="col-xs-12" id="news">
<h2 style="color:red;">News</h2>
<ul>
<li>Accepted paper list published. See <a href="#papers" target="_blank">Papers</a>.<br/>
<a href="#program" target="_blank">Program</a> announced -
<span style="color:red;"><strong>KDD registration required to access the platform</strong>.
</li>
<li>Paper submission deadline extended to
<span style="color:red;"><strong>Jun 01, 2021</strong></span>.
<a href="#dates" target="_blank">See updated dates</a>
</li>
<li><b>KDD Health Day and DSHealth will be held jointly this year</b></li>
<li>Selected papers will be invited to publish in a special issue of
<a href="https://www.sciencedirect.com/journal/artificial-intelligence-in-medicine" target="_blank">Artificial Intelligence in Medicine</a>
journal. Please see updated <a href="#call" target="_blank">CFP</a>
</li>
<li><a href="#speaker-banner">Invited Speaker</a> lineup published. </li>
<!-- Selected papers will be part of the KDD Health Day poster -->
<!-- session in the evening. -->
<!-- See <a href="#papers" target="_blank">Papers</a>.</li> -->
<!-- <li>Paper acceptance notification updated to Jun 12, 2019</li> -->
<!-- [> <li>Flyer released <a href="MLMH2018_Flyer.pdf" target="_blank">See Here</a></li> <] -->
<!-- <li><strong>Announcing $500 travel grant each for the best paper and the best student paper, -->
<!-- selected for the workshop. -->
<!-- Please see updated <a href="#call" target="_blank">call for papers</a>. </strong></li> -->
<!-- [> <li>We have been selected to be part of <] -->
<!-- [> <a href="http://www.kdd.org/kdd2018/health-day-at-kdd" target="_blank">KDD Health Day</a> <] -->
<!-- [> </li> <] -->
</ul>
</div>
<div class="col-xs-12" id="overview">
<h2>Overview</h2>
<p>
Healthcare is, traditionally, a knowledge-driven enterprise with an enormous
amount of data - both structured and unstructured. These data can impact
positively on the development of data-driven health care including precision
medicine and precision public health. In recent years, large scale
medical/clinical datasets, such as “omics” data and radiology reports are
increasingly available. We have also witnessed an increasing number of
successful AI/ML applications using such datasets to address problems such as
drug repurposing and preliminary screening of radiology reports. To facilitate
the adoption of such AI/ML in practice, we have simultaneously witnessed an
increasing adoption/innovation of using explainability methods to
analyze/present AI for Health. In this deep learning era, What is the current
status of AI/ML applications in healthcare? What are the standard methods of
explaining such AI models for healthcare? What are the roles of causality in
AI/ML practices? What are the state-of-the-art developments in causal AI in
health and health care domains? What are the limitations and how are the
different facets of trust and explanations (see figure 1 below) being addressed
in practice? Can knowledge-backed AI lead to more robust and interpretable
models? How do data scientists and physicians apply this knowledge in
collaboration and via human-centered AI approaches to further the field and
improve healthcare? How are regulatory requirements for transparency and
trustworthiness of models and data privacy being defined and how can they be
fulfilled?
After witnessing so many great achievements from deep learning lately, we
propose to invite world-leading experts from both data science and healthcare
to discuss and debate the path forward for practical applications of AI/ML in
healthcare, including demos, early work, and critiques on the current state and
the path forward for explainability and trustworthiness in AI. More
specifically, we plan to attract high-quality original research from emerging
areas with significant implications in healthcare and invite open discussions
on controversial yet crucial topics regarding healthcare transformation
</p>
<h2>Previous Iterations</h2>
<ul>
<li><a href="https://dshealthkdd.github.io/dshealth-2020/" target="_blank">DSHealth 2020</a>:
2020 KDD Workshop on Applied Data Science for Healthcare: Trustable and Actionable AI for Healthcare
</li>
<li><a href="https://dshealthkdd.github.io/dshealth-2019/" target="_blank">DSHealth 2019</a>:
2019 KDD Workshop on Applied Data Science for Healthcare: Bridging the Gap between Data and Knowledge
</li>
<li><a href="https://mlmhworkshop.github.io/mlmh-2018/" target="_blank">MLMH 2018</a>:
2018 KDD Workshop on Machine Learning for Medicine and Healthcare
</li>
</ul>
<!-- </div> -->
<!-- <div class="row" id="speaker-banner"> -->
<h2>Invited Speakers</h2>
<div class="col-md-12" id="speaker-banner">
<div class="col-md-3">
<img class="img-responsive img-circle" src="./assets/mihaela_van_der_schaar.jpeg"
style="max-height: 150px;"
alt="Profile Image"></img> <br/>
<a href="https://www.vanderschaar-lab.com/prof-mihaela-van-der-schaar/" target="_blank">Mihaela Van Der Schaar</a>
<br/>
<span>John Humphrey Plummer Professor of Machine Learning, AI, and Medicine at University of Cambridge</span>
</div>
<div class="col-md-3">
<img class="img-responsive img-circle" src="./assets/alexej_gossman.jpeg"
style="max-height: 150px;"
alt="Profile Image"></img> <br/>
<a href="https://www.linkedin.com/in/alexejgossmann/" target="_blank">Alexej Gossmann</a>
<br/>
<span>Staff Fellow (Mathematical Statistician) at FDA</span>
</div>
<div class="col-md-3">
<img class="img-responsive img-circle" src="./assets/fernando_schwarz.jpeg"
style="max-height: 150px;"
alt="Profile Image"></img> <br/>
<a href="https://www.linkedin.com/in/fernandoschwartz" target="_blank">Fernando Schwartz</a>
<br/>
<span>Global Head of Data Science, Merck</span>
</div>
<div class="col-md-3">
<img class="img-responsive img-circle" src="./assets/leo_celi.jpeg"
style="max-height: 150px;"
alt="Profile Image"></img> <br/>
<a href="https://imes.mit.edu/research-staff-prof/leo-anthony-celi/" target="_blank">Leo Celi</a>
<br/>
<span>Principal Research Scientist, MIT; Co-Director, MIT Sana; Staff Physician, Beth Israel Deaconess Medical Center; Assoc. Prof, Harvard Medical School
</span>
</div>
</div>
<div class="col-md-12">
<div class="col-md-3">
<img class="img-responsive img-circle" src="./assets/gunther_jansen.png"
style="max-height: 150px;"
alt="Profile Image"></img> <br/>
<a href="https://www.linkedin.com/in/gunther-jansen-phd/" target="_blank">Gunther Jansen</a>
<br/>
<span>Head of PHC analytics, Roche</span>
</div>
<div class="col-md-3">
<img class="img-responsive img-circle" src="./assets/william_kassler.jpeg"
style="max-height: 150px;"
alt="Profile Image"></img> <br/>
<a href="https://www.linkedin.com/in/william-kassler/" target="_blank">William Kassler</a>
<br/>
<span>CMO, Palantir Technology Inc.</span>
</div>
<div class="col-md-3">
<img class="img-responsive img-circle" src="./assets/gretchen_purcell_jackson.jpeg"
style="max-height: 150px;"
alt="Profile Image"></img> <br/>
<a href="https://www.amia.org/about-amia/leadership/officer/gretchen-purcell-jackson-md-phd-facs-facmi-famia" target="_blank">Gretchen Purcell Jackson</a>
<br/>
<span> Vice President and Chief Science Officer, IBM, Watson Health</span>
</div>
<div class="col-md-3">
<img class="img-responsive img-circle" src="./assets/dave_de_caprio.jpeg"
style="max-height: 150px;"
alt="Profile Image"></img> <br/>
<a href="https://www.linkedin.com/in/davedecaprio/" target="_blank">Dave DeCaprio</a>
<br/>
<span>CTO and Co-founder at ClosedLoop.ai</span>
</div>
</div>
</div>
<!-- [> end speaker banner <] -->
</div>
<!-- end workshop description -->
<div role="tabpanel" class="tab-pane" id="program"><br>
<h2>Program</h2>
<p>Joint KDD Health Day - DSHealth 2021 will be held
on August 15-16, 2021, SGT. See detailed schedule below.
Selected papers will be invited to publish in a special issue of
<a href="https://www.sciencedirect.com/journal/artificial-intelligence-in-medicine" target="_blank">Artificial Intelligence in Medicine</a>
journal.
</p>
<br/>
<br/>
Please refer to the <a href="https://www.kdd.org/kdd2021/#" target="_blank">KDD 2021 program</a>
for up-to-date changes on venues and timings.
</p>
<div class="col-xm-12">
<h3>DSHealth Schedule</h3>
<p>Venue: Virtual. (Zoom link will be provided in the KDD virtual conference app - KDD registration is required)
<!-- <button type="button" class="btn btn-sm btn-secondary"> -->
<!-- <a href="https://kddvirtual2020.vfairs.com" target="_blank">KDD Virtual Conference Link</a> -->
<!-- </button> -->
<!-- <button type="button" class="btn btn-sm btn-secondary"> -->
<!-- <a href="https://whova.com/portal/webapp/kdd_202008/Agenda/1140638" target="_blank">Whova link</a> -->
<!-- </button> -->
</p>
<div class="table-responsive" >
<table class="table table-hover">
<thead>
<th class="col-md-2">SGT</th>
<th class="col-md-2">CEST</th>
<th class="col-md-2">EDT</th>
<th class="col-md-2">PDT</th>
<th class="col-md-4">Event</th>
</thead>
<tbody>
<tr class = "info">
<td>Aug 15, <br/>11:00 pm - 3:00 am (+1)</td>
<td>Aug 15, <br/>5:00 pm - 9:00 pm</td>
<td>Aug 15, <br/>11:00 am - 3:00 pm</td>
<td>Aug 15, <br/>08:00 am - 12:00 pm</td>
<td>Session 1</td>
</tr>
<tr >
<td>11:00 pm - 11:10 pm</td>
<td>5:00 pm - 5:10 pm</td>
<td>11:00 am - 11:10 am</td>
<td>8:00 am - 8:10 am</td>
<td>Introduction</td>
</tr>
<tr class = "active">
<td>11:10 pm - 11:50 pm</td>
<td>5:10 pm - 5:50 pm</td>
<td>11:10 am - 11:50 am</td>
<td>8:10 am - 8:50 am</td>
<td>Invited Talk:<br/>Mihaela Van Der Schaar</td>
</tr>
<tr >
<td>11:50 pm - 00:30 am (+1)</td>
<td>5:50 pm - 6:30 pm</td>
<td>11:50 am - 12:30 pm</td>
<td>8:50 am - 9:30 am</td>
<td>Spotlight Presentation 1<br/>
<br/>
<strong>#20: </strong>Midwifery Learning and Forecasting: Predicting Content Demand with User-Generated Logs<br/>
<strong>#21: </strong>On the Use of Time Series Kernel and Dimensionality Reduction to Identify the Acquisition of Antimicrobial Multidrug Resistance in the Intensive Care Unit<br/>
<strong>#22: </strong>Encoding Domain Information with Sparse Priors for Inferring Explainable Latent Variables<br/>
<strong>#16: </strong>Automatic Seizure Detection Using the Pulse Transit Time<br/>
<strong>#18: </strong>GAN-based Data Augmentation for Chest X-ray Classification<br/>
<strong>#8: </strong>Leveraging Clinical Context for User-Centered Explainability: A Diabetes Use Case<br/>
<strong>#23: </strong>Exploring the Scope and Potential of Local Newspaper-based Dengue Surveillance in Bangladesh<br/>
<strong>#12: </strong>Predicting Disease Progress with Imprecise Lab Test Results
</td>
</tr>
<tr class = "info">
<td>00:30 am - 1:00 am</td>
<td>6:30 pm - 7:00 pm</td>
<td>12:30 pm - 1:00 pm</td>
<td>9:30 am - 10: am</td>
<td>Break</td>
</tr>
<tr >
<td>1:00 am - 1:40 am</td>
<td>7:00 pm - 7:40 pm</td>
<td>1:00 pm - 1:40 pm</td>
<td>10:00 am - 10:40 am</td>
<td>Invited talk:<br/>Gunther Jansen</td>
</tr>
<tr class = "active">
<td>1:40 am - 2:20 am</td>
<td>7:40 pm - 8:20 pm</td>
<td>1:40 pm - 2:20 pm</td>
<td>10:40 am - 11:20 am</td>
<td>Invited Talk:<br/>Alexej Gossmann</td>
</tr>
<tr >
<td>2:20 am - 3:00 am</td>
<td>8:20 pm - 9:00 pm</td>
<td>2:20 pm - 3:00 pm</td>
<td>11:20 - 12:00 pm</td>
<td>Invited Talk:<br/>William Kassler</td>
</tr>
<tr class = "info">
<td>3:00 am - 4:00 am</td>
<td>9:00 pm - 10:00 pm</td>
<td>3:00 pm - 4:00 pm</td>
<td>12:00 pm - 1:00 pm</td>
<td>Break</td>
</tr>
<tr class = "info">
<td>Aug 16,<br/>4:00 am - 8:00 am</td>
<td>Aug 15, <br/>10:00 pm - 02:00 am (+1)</td>
<td>Aug 15, <br/>4:00 pm - 8:00 pm</td>
<td>Aug 15, <br/>1:00 pm - 5:00 pm</td>
<td>Session 2</td>
</tr>
<tr >
<td>4:00 am - 4:10 am</td>
<td>10:00 pm - 10:10 pm</td>
<td>4:00 pm - 4:10 pm</td>
<td>1:00 pm - 1:10 pm</td>
<td>Best paper anouncements</td>
</tr>
<tr class = "active">
<td>4:10 am - 4:50 am</td>
<td>10:10 pm - 10:50 pm</td>
<td>4:10 pm - 4:50 pm</td>
<td>1:10 pm - 1:50 pm</td>
<td>Invited Talk:<br/>Fernando Schwartz</td>
</tr>
<tr >
<td>4:50 am - 5:30 am</td>
<td>10:50 pm - 11:30 pm</td>
<td>4:50 pm - 5:30 pm</td>
<td>1:50 pm - 2:30 pm</td>
<td>Invited Talk:<br/>Leo Celi</td>
</tr>
<tr class = "info">
<td>5:30 am - 6:00 am</td>
<td>11:30 pm - 00:00 am (+1)</td>
<td>5:30 pm - 6:00 pm</td>
<td>2:30 pm - 3:00 pm</td>
<td>Break</td>
</tr>
<tr >
<td>6:00 am - 6:40 am</td>
<td>00:00 am - 00:40 am</td>
<td>6:00 pm - 6:40 pm</td>
<td>3:00 pm - 3:40 pm</td>
<td>Invited Talk:<br/>Gretchen Purcell Jackson</td>
</tr>
<tr class = "active">
<td>6:40 am - 7:20 am</td>
<td>00:40 am - 1:20 am</td>
<td>6:40 pm - 7:20 pm</td>
<td>3:40 pm - 4:20 pm</td>
<td>Invited Talk:<br/>Dave DeCaprio</td>
</tr>
<tr >
<td>7:20 am - 7:50 am</td>
<td>1:20 am - 1:50 am</td>
<td>7:20 pm - 7:50 pm</td>
<td>4:20 pm - 4:50 pm</td>
<td>Spotlight Presentation 2<br/>
<br/>
<strong>#14: </strong>Time Series Classification Towards Mobile Health and Remote Monitoring of Patients: Case Study on Epilepsy Disease<br/>
<strong>#7: </strong>Towards a fairer reimbursement system for burn patients using cost-sensitive classification<br/>
<strong>#13: </strong>Quantifying machine learning-induced overdiagnosis in sepsis<br/>
<strong>#10: </strong>Assessing putative bias in prediction of anti-microbial resistance from real-world genotyping data under explicit causal assumptions<br/>
<strong>#6: </strong>The Future will be Different than Today: Model Evaluation Considerations when Developing Translational Clinical Biomarker<br/>
</td>
</tr>
<tr class = "active">
<td>7:50 am - 8:00 am</td>
<td>1:50 am - 2:00 am</td>
<td>7:50 pm - 8:00 pm</td>
<td>4:50 pm - 5:00 pm</td>
<td>Closing session</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
<!-- end program -->
<!-- <div role="tabpanel" class="tab-pane" id="speakers"><br> -->
<!-- <h2>Invited Speaker</h2> -->
<!-- <div class="col-md-12" id="speaker-1"> -->
<!-- <h4><a href="https://www.hwanglab.org/" target="_blank"> -->
<!-- <span class="glyphicon glyphicon-globe"/> -->
<!-- </a> -->
<!-- Dr. Tae Hyun Hwang, Cleveland Clinic Lerner College of Medicine, USA. -->
<!-- </h4> -->
<!-- <br/> -->
<!-- <div class="row"> -->
<!-- <div class="col-md-10 col-sm-12"> -->
<!-- <p><strong>Bio:</strong> -->
<!-- Tae Hyun Hwang received his Ph.D. in Computer Science (Machine Learning and -->
<!-- Computational Biology) at the University of Minnesota Twin-Cites at 2011. He and his research -->
<!-- group lead machine learning and AI research at the Cleveland Clinic. Prior to his appointment at the Cleveland Clinic, he was a Research Associate in the Department of Computational Biology and Bioinformatics at Genentech and was a tenure-track faculty at the University of Texas -->
<!-- Southwestern Medical Center (UTSW) where he served as a co-director for UTSW Kidney -->
<!-- Cancer SPORE and led a computational team for UT Lung Cancer SPORE. He currently serves as a bioinformatics core director for NASA Specialized Centers of Research (NSCOR) as well as committees of various Machine Learning, Data Mining, and AI conferences. -->
<!-- <br/> -->
<!-- He and his lab members from Translational Machine Learning and AI lab at the Cleveland Clinic are working on developing novel machine learning and AI algorithms that are readily applicable in the clinical setting to help patients with a lethal disease. His work has been published more -->
<!-- than 40 peer-reviewed journals such as Nature, Cell, Nature Neuroscience, and Cancer Cell, as -->
<!-- well as top machine learning, data mining and AI conferences including IEEE International -->
<!-- Conference on Data Mining (ICDM) and SIAM International Conference on Data Mining (SDM). -->
<!-- He is a recipient of the American Cancer Society Young Investigator Award and NCI UTSW-MD -->
<!-- Anderson Lung Cancer SPORE Career Development Award. -->
<!-- </p> -->
<!-- </div> -->
<!-- <div class="col-md-2 hidden-sm hidden-xs pull-right"> -->
<!-- <img class="img-responsive img-circle" src="./assets/tae_hyun_hwang.jpg" -->
<!-- style="max-height: 150px;" -->
<!-- alt="Profile Image"></img> -->
<!-- </div> -->
<!-- </div> -->
<!-- <div class="table-responsive"> -->
<!-- <table class="table table-borderless"> -->
<!-- <tr> -->
<!-- <td class="col-sm-1"><span class="glyphicon glyphicon-bullhorn"></span> Title</em></td> -->
<!-- <td class="col-sm-11"> Deploying AI in healthcare in the wild: Lessons, challenges, and opportunities -->
<!-- </td> -->
<!-- </tr> -->
<!-- <tr> -->
<!-- <td><span class="glyphicon glyphicon-calendar"></span> Time</em></td> -->
<!-- <td>10:00 am - 10:30 am</td> -->
<!-- </tr> -->
<!-- <tr> -->
<!-- <td><span class="glyphicon glyphicon-home"></span> Venue</em></td> -->
<!-- <td>Cook - Street Level, Egan</td> -->
<!-- </tr> -->
<!-- </table> -->
<!-- </div> -->
<!-- </div> -->
<!-- [> end speaker 1 <] -->
<!-- <h2>Panel</h2> -->
<!-- <br/> -->
<!-- <div class="row" id="speaker-2"> -->
<!-- <div class="col-md-4"> -->
<!-- <div class="table-responsive"> -->
<!-- <table class="table table-borderless"> -->
<!-- <tr> -->
<!-- <td class="col-sm-4"><span class="glyphicon glyphicon-bullhorn"></span> Topic</em></td> -->
<!-- <td class="col-sm-8">Relevance and importance of knowledge -->
<!-- driven AI, in order to address real challenges and make an -->
<!-- impact in healthcare -->
<!-- </td> -->
<!-- </tr> -->
<!-- <tr> -->
<!-- <td><span class="glyphicon glyphicon-calendar"></span> Time</em></td> -->
<!-- <td>3:40 pm - 4:30 pm</td> -->
<!-- </tr> -->
<!-- <tr> -->
<!-- <td><span class="glyphicon glyphicon-home"></span> Venue</em></td> -->
<!-- <td>Summit 3 - Ground Level, Egan</td> -->
<!-- </tr> -->
<!-- </table> -->
<!-- </div> -->
<!-- </div> -->
<!-- <div class="col-md-8"> -->
<!-- <div class="col-md-2"> -->
<!-- <img class="img-responsive img-circle" src="./assets/fred_rahmanian.jpeg" -->
<!-- style="max-height: 150px;" -->
<!-- alt="Profile Image"></img> <br/> -->
<!-- <a href="https://www.linkedin.com/in/fredrahmanian/" target="_blank">Fred Rahmanian</a> -->
<!-- <strong>(Moderator)</strong> -->
<!-- </div> -->
<!-- <div class="col-md-2"> -->
<!-- <img class="img-responsive img-circle" src="./assets/jasmine_wilkerson.jpeg" -->
<!-- style="max-height: 150px;" -->
<!-- alt="Profile Image"></img> <br/> -->
<!-- <a href="https://www.linkedin.com/in/jasmine-wilkerson/" target="_blank">Jasmine Wilkerson</a> -->
<!-- </div> -->
<!-- <div class="col-md-2"> -->
<!-- <img class="img-responsive img-circle" src="./assets/lisa_weavind.jpg" -->
<!-- style="max-height: 150px;" -->
<!-- alt="Profile Image"></img> <br/> -->
<!-- <a href="https://www.vumc.org/burn/person/lisa-weavind-md" target="_blank">Lisa Weavind</a> -->
<!-- </div> -->
<!-- <div class="col-md-2"> -->
<!-- <img class="img-responsive img-circle" src="./assets/fei_wang.jpeg" -->
<!-- style="max-height: 150px;" -->
<!-- alt="Profile Image"></img> <br/> -->
<!-- <a href="https://sites.google.com/site/feiwang03/" target="_blank">Fei Wang</a> -->
<!-- </div> -->
<!-- <div class="col-md-2"> -->
<!-- <img class="img-responsive img-circle" src="./assets/maria_Spiliopoulou.png" -->
<!-- style="max-height: 150px;" -->
<!-- alt="Profile Image"></img> <br/> -->
<!-- <a href="http://www.kmd.ovgu.de/Team/Academic+Staff/Myra+Spiliopoulou.html" target="_blank">Maria Spiliopoulou</a> -->
<!-- </div> -->
<!-- </div> -->
<!-- </div> -->
<!-- [> end speaker 1 <] -->
<!-- </div> -->
<!-- end speakers -->
<div role="tabpanel" class="tab-pane" id="papers"><br>
<h2>Accepted Papers</h2>
<p>
We have accepted 13papers for presentation at the workshop. All papers
will be presented as posters within the workshop.
PDF version of the final papers, if provided by the authors, are hyperlinked below.
</p>
<div class="col-xm-12">
<h3>Spotlight Presentations</h3>
<table class="table table-borderless">
<tbody>
<tr><td>
<strong>#6 </strong>
<a href='https://arxiv.org/abs/2107.08787' target='_blank'>The Future will be Different than Today: Model Evaluation Considerations when Developing Translational Clinical Biomarker</a><br/>
<em>Yichen Lu, Jane Fridlyand, Tiffany Tang, Nina Qi, Noah Simon and Ning Leng</em>
</td></tr>
<tr><td>
<strong>#7 </strong>
<a href='https://arxiv.org/abs/2107.00531' target='_blank'>Towards a fairer reimbursement system for burn patients using cost-sensitive classification</a><br/>
<em>Chimdimma Noelyn Onah, Richard Allmendinger, Julia Handl and Ken Dunn</em>
</td></tr>
<tr><td>
<strong>#8 </strong>
<a href='https://arxiv.org/abs/2107.02359' target='_blank'>Leveraging Clinical Context for User-Centered Explainability: A Diabetes Use Case</a><br/>
<em>Shruthi Chari, Prithwish Chakraborty, Mohamed Ghalwash, Oshani Seneviratne, Elif K. Eyigoz, Daniel M. Gruen, Fernando Suarez Saiz, Ching-Hua Chen, Pablo Meyer Rojas, and Deborah L. McGuinness</em>
<button type="button" class="btn btn-sm btn-success" disabled><i class="fa fa-trophy"></i> Best Paper </button>
</td></tr>
<tr><td>
<strong>#10 </strong>
<a href='https://arxiv.org/abs/2107.03383' target='_blank'>Assessing putative bias in prediction of anti-microbial resistance from real-world genotyping data under explicit causal assumptions</a><br/>
<em>Mattia Prosperi, Simone Marini, Christina Boucher and Jiang Bian</em>
</td></tr>
<tr><td>
<strong>#12 </strong>
<a href='https://arxiv.org/abs/2107.03620' target='_blank'>Predicting Disease Progress with Imprecise Lab Test Results</a><br/>
<em>Mei Wang, Jianwen Su and Zhihua Lin</em>
<button type="button" class="btn btn-sm btn-success" disabled><i class="fa fa-trophy"></i> Best Paper </button>
</td></tr>
<tr><td>
<strong>#13 </strong>
<a href='http://arxiv.org/abs/2107.10399' target='_blank'>Quantifying machine learning-induced overdiagnosis in sepsis</a><br/>
<em>Anna Fedyukova, Daniel Capurro and Douglas Pires</em>
</td></tr>
<tr><td>
<strong>#14 </strong>
<a href='https://drive.google.com/file/d/1eHoZ8G3lFJf7P3oD5s6NSVmpelmfuIeN/view?usp=sharing' target='_blank'>Time Series Classification Towards Mobile Health and Remote Monitoring of Patients: Case Study on Epilepsy Disease</a><br/>
<em>Arman Abdoli, Mohammadreza Majma and Parisa Rahmani</em>
</td></tr>
<tr><td>
<strong>#16 </strong>
<a href='http://arxiv.org/abs/2107.05894' target='_blank'>Automatic Seizure Detection Using the Pulse Transit Time</a><br/>
<em>Eric Fiege, Salima Houta, Pinar Bisgin, Rainer Surges and Falk Howar</em>
</td></tr>
<tr><td>
<strong>#18 </strong>
<a href='https://arxiv.org/abs/2107.02970' target='_blank'>GAN-based Data Augmentation for Chest X-ray Classification</a><br/>
<em>Neha Hulkund and Shobhita Sundaram</em>
</td></tr>
<tr><td>
<strong>#20 </strong>
<a href='https://arxiv.org/abs/2107.02480' target='_blank'>Midwifery Learning and Forecasting: Predicting Content Demand with User-Generated Logs</a><br/>
<em>Anna Guitart Atienza, Ana Fernández del Río, África Periáñez and Lauren Bellhouse</em>
<button type="button" class="btn btn-sm btn-success" disabled><i class="fa fa-trophy"></i> Best Paper </button>
</td></tr>
<tr><td>
<strong>#21 </strong>
<a href='https://arxiv.org/abs/2107.10398' target='_blank'>On the Use of Time Series Kernel and Dimensionality Reduction to Identify the Acquisition of Antimicrobial Multidrug Resistance in the Intensive Care Unit</a><br/>
<em>Óscar Escudero-Arnanz, Joaquín Álvarez-Rodríguez, Karl Øyvind Mikalsen, Robert Jenssen and Cristina Soguero-Ruiz</em>
</td></tr>
<tr><td>
<strong>#22 </strong>
<a href='https://arxiv.org/abs/2107.03730' target='_blank'>Encoding Domain Information with Sparse Priors for Inferring Explainable Latent Variables</a><br/>
<em>Arber Qoku and Florian Buettner</em>
</td></tr>
<tr><td>
<strong>#23 </strong>
<a href='https://arxiv.org/abs/2107.14095' target='_blank'>Exploring the Scope and Potential of Local Newspaper-based Dengue Surveillance in Bangladesh</a><br/>
<em>Md. Istiak Hossain Shihab, Nazia Tasnim, Sheikh Rabiul Islam and Mohammad Ruhul Amin</em>
</td></tr>
</tbody>
</table>
</div>
</div>
<!-- end papers -->
<div role="tabpanel" class="tab-pane" id="call"><br>
<h2>Call for Papers</h2>
<p>We invite full papers, as well as work-in-progress on the application
of data science in healthcare.
Topics may include, but not limited to, the following topics (For more information
see <a href="#home" target="_blank">workshop overview</a>) with special
focus on papers that are aimed at addressing the state of explainable and trustworthiness of AI in healthcare.
</p>
<ul>
<li>Applications of XAI in Healthcare</li>
<li>Critique of XAI in Healthcare</li>
<li>User driven XAI in Healthcare</li>
<li>Trustworthiness</li>
<li>Uncertainty quantification and communication, e.g. out-of-distribution detection</li>
<li>Domain generalization and adaptation, e.g. multi-site studies</li>
<li>Data access, sharing and privacy, e.g. via federated learning</li>
<li>Human-in-the-loop-learning and human-centered AI</li>
<li>Synthetic data for healthcare research</li>
<li>Interpretable healthcare</li>
<li>Actionable Insights</li>
<li>Behavioral studies</li>
<li>Ethical AI and accountability</li>
<li>Regulatory aspects of AI in healthcare</li>
<li>Nudging and implications</li>
<li>Multidisciplinary studies on Healthcare</li>
<li>Demos of practical applications</li>
</ul>
<p>Papers must be submitted in PDF format to easychair
<a href="https://easychair.org/conferences/?conf=dshealth2021"
target="_blank">https://easychair.org/conferences/?conf=dshealth2021</a>
and formatted according to the new
<a href="https://www.acm.org/publications/proceedings-template" target="_blank">
Standard ACM Conference Proceedings Template
</a>.
Authors are encouraged to use the
<a href="https://www.overleaf.com/latex/templates/acm-conference-proceedings-primary-article-template/wbvnghjbzwpc" target="_blank">
Overleaf template
</a>.
Papers must be a maximum length of 4 pages, excluding references.
</p>
<p>The program committee will select the papers based on originality, presentation,
and technical quality for spotlight and/or poster presentation.</p>
<p style="color:darkblue">Selected papers will be invited to publish in a special issue of
<a href="https://www.sciencedirect.com/journal/artificial-intelligence-in-medicine" target="_blank">Artificial Intelligence in Medicine</a>
journal
</p>
<!-- <p class="text-info"><strong> -->
<!-- The best paper and the best student paper will be awarded 500 travel grant each. -->
<!-- Please indicate whether the primary author is a student in the easychair submission form. -->
<!-- </strong></p> -->
</div>
<!-- end call -->
<div role="tabpanel" class="tab-pane" id="dates"><br>
<h2>Key Dates</h2>
<ul>
<li> Paper Submission opens: Apr 15, 2021</li>
<li> <b>Paper Submission deadline: <strike>May 20, 2021</strike> Jun 01, 2021</b></li>
<li>Acceptance Notice: <strike>Jun 20, 2021</strike> Jun 25, 2021</li>
<li>Workshop Date: Aug 14-18, 2021</li>
</ul>
<p>All deadlines correspond to 11:59 PM Hawaii Standard Time
(<a href="https://www.timeanddate.com/worldclock/usa/honolulu" target="_blank"> HST</a>).
<!-- For any questions / concerns, please contact us at <a href="mailto:[email protected]" target="_blank">[email protected]</a>. -->
</p>
</div>
<!-- end dates -->
<div role="tabpanel" class="tab-pane" id="organizers"><br>
<h2>Organizers</h2>
<ul>
<li><a href="https://wcm-wanglab.github.io/index.html" target="_blank">Fei Wang</a>, Cornell University, USA</li>
<li><a href="https://prithwi.github.io" target="_blank">Prithwish Chakraborty</a>, IBM Research, USA</li>
<li><a href="https://scholar.google.com/citations?user=FyNfOOQAAAAJ&hl=en" target="_blank">Tao Xu</a>, F-Hoffmann la Roche, Switzerland</li>
<li><a href="https://www.linkedin.com/in/pyhsueh/" target="_blank">Pei-Yun Sabrina Hsueh</a>, Bayesian Health Inc, USA</li>
<li><a href="https://www.slds.stat.uni-muenchen.de/people/Xudong/" target="_blank">Xudong Sun</a>, LMU Munich, Germany</li>
<li><a href="http://www.ri.fzv.um.si/gstiglic/" target="_blank">Gregor Stiglic</a>, University of Maribor, Slovenia</li>
<li><a href="https://www.linkedin.com/in/gracy-crane-374ba120/?originalSubdomain=uk" target="_blank">Gracy Crane</a>, Roche Products Ltd</li>
<li><a href="https://www.mdc-berlin.de/haghverdi" target="_blank">Laleh Haghverdi</a>, Max-Delbrueck Center for Molecular Medicine, Germany</li>
<li><a href="https://hobi.med.ufl.edu/profile/bian-jiang/" target="_blank">Jiang Bian</a>, University of Florida, USA</li>
<li><a href="https://www.linkedin.com/in/yaolixia" target="_blank">Lixia Yao</a>, Merck, USA</li>
<li><a href="https://scholar.google.com/citations?user=AaPKbPAAAAAJ&hl=en" target="_blank">Florian Buettner</a>, Frankfurt University/German Cancer Research Center (DKFZ), Germany</li>
</ul>
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