BioData Mining

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Topical areas include, but are not limited to: Development, evaluation, and application of novel data mining and machine learning algorithms. Adaptation, evaluation, and application of traditional data mining and machine learning algorithms. Open-source software for the application of data mining and machine learning algorithms. Design, development and integration of databases, software and web services for the storage, management, retrieval, and analysis of data from large scale studies. Pre-processing, post-processing, modeling, and interpretation of data mining and machine learning results for biological interpretation and knowledge discovery. Data types include Imaging Electronic health records Biobanks Environmental data Social and behavioral data Wearable devices Social media data</pre><div class="alert alert-warning"> Last updated by <a href="/researcher/1">Dou Sun</a> in 2024-07-20</div> </div> </div>  <div class="portlet" id="yw3"> <div class="portlet-decoration"> <div class="portlet-title"><i class="icon icon-file"></i> Related Journals</div> </div> <div class="portlet-content"> <div class="hidden-phone"> <div id="yw4" class="grid-view"> <table class="table table-hover table-striped table-bordered table-condensed"> <thead> <tr> <th id="yw4_c0">CCF</th><th id="yw4_c1">Full Name</th><th id="yw4_c2">Impact Factor</th><th id="yw4_c3">Publisher</th><th id="yw4_c4">ISSN</th></tr> </thead> <tbody> <tr class="odd"> <td><span class="badge badge-warning">b</span></td><td><a href="/journal/143">Computer Aided Geometric Design</a></td><td>1.300</td><td>Elsevier</td><td>0167-8396</td></tr> <tr class="even"> <td></td><td><a 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