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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=clinical+trial">
  <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
  <link><![CDATA[http://ebiquity.umbc.edu//tags/html/?t=clinical+trial]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for clinical trial]]></description>
  <items>
    <rdf:Seq>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/101/MTLD-Interpreting-Medical-Tables-as-Linked-Data"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/742/Clinico-genomic-Data-Analytics-for-Precision-Diagnosis-and-Disease-Management"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/743/Collaborative-data-mining-for-clinical-trial-analytics"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/744/Poster-Classifying-primary-outcomes-in-rheumatoid-arthritis-Knowledge-discovery-from-clinical-trial-metadata"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/745/SQL-like-big-data-environments-Case-study-in-clinical-trial-analytics"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/692/TABEL-A-Domain-Independent-and-Extensible-Framework-for-Inferring-the-Semantics-of-Tables"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/661/Interpreting-Medical-Tables-as-Linked-Data-to-Generate-Meta-Analysis-Reports"/>
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 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/101/MTLD-Interpreting-Medical-Tables-as-Linked-Data">
  <title><![CDATA[MTLD: Interpreting Medical Tables as Linked Data]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/101/MTLD-Interpreting-Medical-Tables-as-Linked-Data</link>
  <description><![CDATA[Evidence-based medicine is the application of current medical evidence
to patient care and typically uses quantitative data from research
studies.  It is increasingly driven by data on the efficacy of drug
dosages and the correlation between various medical factors that is
assembled and integrated through meta--analyses (i.e., systematic
reviews) of data in tables from publications and clinical trial
studies.  We describe a a key component of a system to produce
evidence reports that p...]]></description>
  <dc:date>2014-01-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/742/Clinico-genomic-Data-Analytics-for-Precision-Diagnosis-and-Disease-Management">
  <title><![CDATA[Clinico-genomic Data Analytics for Precision Diagnosis and Disease Management]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/742/Clinico-genomic-Data-Analytics-for-Precision-Diagnosis-and-Disease-Management</link>
  <description><![CDATA[Patient data can be present in clinical notes, lab results, genomic data sources, environmental and geospatial data sources and tissue banks to name a few. A holistic view of the patient's health can be achieved when relevant data from multiple heterogeneous sources are extracted and analyzed in a personalized manner. Moreover, comparative analysis of patients can be performed when multiple patient records are viewed across these heterogeneous data sources. To address this need, we propose cl...]]></description>
  <dc:date>2015-11-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/743/Collaborative-data-mining-for-clinical-trial-analytics">
  <title><![CDATA[Collaborative data mining for clinical trial analytics]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/743/Collaborative-data-mining-for-clinical-trial-analytics</link>
  <description><![CDATA[his paper proposes a collaborative data mining technique to provide multi-level analysis from clinical trials data. Clinical trials for clinical research and drug development generate large amount of data. Due to dispersed nature of clinical trial data, it remains a challenge to harness this data for analytics. In this paper, we propose a novel method using master data management (MDM) for analyzing clinical trial data, scattered across multiple databases, through collaborative data mining. O...]]></description>
  <dc:date>2015-11-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/744/Poster-Classifying-primary-outcomes-in-rheumatoid-arthritis-Knowledge-discovery-from-clinical-trial-metadata">
  <title><![CDATA[Poster: Classifying primary outcomes in rheumatoid arthritis: Knowledge discovery from clinical trial metadata]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/744/Poster-Classifying-primary-outcomes-in-rheumatoid-arthritis-Knowledge-discovery-from-clinical-trial-metadata</link>
  <description><![CDATA[Early prediction of treatment outcomes in RA clinical trials is critical for both patient safety and trial success. We hypothesize that an approach employing metadata of clinical trials could provide accurate classification of primary outcomes before trial implementation. We retrieved RA clinical trials metadata from ClinicalTrials.gov. Four quantitative outcome measures that are frequently used in RA trials, i.e., ACR20, DAS28, and AE/SAE, were the classification targets in the model. Classi...]]></description>
  <dc:date>2015-11-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/745/SQL-like-big-data-environments-Case-study-in-clinical-trial-analytics">
  <title><![CDATA[SQL-like big data environments: Case study in clinical trial analytics]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/745/SQL-like-big-data-environments-Case-study-in-clinical-trial-analytics</link>
  <description><![CDATA[Big Data deals with enormous volumes of complex and exponentially growing data sets from multiple sources. With rapid growth in technology, we are now able to generate immense amount of data in almost any field imaginable including physical, biological and biomedical sciences. With the diversity and amount of data in health care industry there is an increasing need to evaluate the components in big data frameworks and gauge their adaptability to analytics techniques. However, a key step in ad...]]></description>
  <dc:date>2015-11-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/692/TABEL-A-Domain-Independent-and-Extensible-Framework-for-Inferring-the-Semantics-of-Tables">
  <title><![CDATA[TABEL - A Domain Independent and Extensible Framework for Inferring the Semantics of Tables]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/692/TABEL-A-Domain-Independent-and-Extensible-Framework-for-Inferring-the-Semantics-of-Tables</link>
  <description><![CDATA[Tables are an integral part of documents, reports and Web pages, compactly encoding important information that can be difficult to express in text. Table like structures outside documents, such as spreadsheets, CSV files, log files and databases, are widely used to represent and share information. Many scientific and technical domains use tables to compactly depict information which is difficult to express in text. However, tables remain beyond the scope of regular text processing systems whi...]]></description>
  <dc:date>2015-01-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/661/Interpreting-Medical-Tables-as-Linked-Data-to-Generate-Meta-Analysis-Reports">
  <title><![CDATA[Interpreting Medical Tables as Linked Data to Generate  Meta-Analysis Reports]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/661/Interpreting-Medical-Tables-as-Linked-Data-to-Generate-Meta-Analysis-Reports</link>
  <description><![CDATA[Evidence-based medicine is the application of current medical evidence to patient care and typically uses quantitative data from research studies.  It is increasingly driven by data on the efficacy of drug dosages and the correlations between various medical factors that are assembled and integrated through meta--analyses (i.e., systematic reviews) of data in tables from publications and clinical trial studies.  We describe a important component of a system to automatically produce evid...]]></description>
  <dc:date>2014-08-13</dc:date>
 </item>
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