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        <article-title>Text mining to enable routine personalized cancer therapy</article-title>
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        <contrib contrib-type="author">
          <string-name>Hua Xu</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
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          <label>0</label>
          <institution>University of Texas Health Science Center Houston</institution>
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          <addr-line>TX</addr-line>
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          <country country="US">USA</country>
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      <abstract>
        <p>-Genomic profiling information is frequently available to oncologists, enabling targeted cancer therapy. Because clinically relevant genomic information is rapidly emerging in narrative data sources such as biomedical literature and clinical trials documents, there is a need for text mining technologies to support targeted therapies. In this talk, we will present two projects about developing text-mining tools to enable personalized cancer therapy, including 1) to identify</p>
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      <p>molecular effects of drugs in biomedical literature, and
2) to create a knowledge base of cancer treatment trials
with annotations about genetic alterations. We believe
such tools would be valuable for physicians and patients
who are seeking information about personalized cancer
therapy, thus facilitating their decision making.</p>
      <p>Keywords— text mining; NLP; precision medicine</p>
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