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    <title>PyPI recent updates for clinicalplan</title>
    <link>https://pypi.org/project/clinicalplan/</link>
    <description>Recent updates to the Python Package Index for clinicalplan</description>
    <language>en</language>    <item>
      <title>0.1.6</title>
      <link>https://pypi.org/project/clinicalplan/0.1.6/</link>
      <description>ClinicalPLAN is a Python package for predicting postoperative risks from clinical notes using language models. It provides training and inference workflows for fine-tuned models, semi-supervised methods, and multi-task prediction of multiple clinical outcomes. The package is intended for clinical research and educational use, notably for the American College of Surgeons.</description>
<author>alba@wustl.edu</author>      <pubDate>Thu, 07 May 2026 05:48:50 GMT</pubDate>
    </item>    <item>
      <title>0.1.5</title>
      <link>https://pypi.org/project/clinicalplan/0.1.5/</link>
      <description>ClinicalPLAN is a Python package for predicting postoperative risks from clinical notes using language models. It provides training and inference workflows for fine-tuned models, semi-supervised methods, and multi-task prediction of multiple clinical outcomes. The package is intended for clinical research and educational use, notably for the American College of Surgeons.</description>
<author>alba@wustl.edu</author>      <pubDate>Thu, 07 May 2026 05:32:37 GMT</pubDate>
    </item>    <item>
      <title>0.1.4</title>
      <link>https://pypi.org/project/clinicalplan/0.1.4/</link>
      <description>ClinicalPLAN is a Python package for predicting postoperative risks from clinical notes using language models. It provides training and inference workflows for fine-tuned models, semi-supervised methods, and multi-task prediction of multiple clinical outcomes. The package is intended for clinical research and educational use, notably for the American College of Surgeons.</description>
<author>alba@wustl.edu</author>      <pubDate>Thu, 30 Apr 2026 14:08:42 GMT</pubDate>
    </item>    <item>
      <title>0.1.3</title>
      <link>https://pypi.org/project/clinicalplan/0.1.3/</link>
      <description>ClinicalPLAN is a Python package for predicting postoperative risks from clinical notes using language models. It provides training and inference workflows for fine-tuned models, semi-supervised methods, and multi-task prediction of multiple clinical outcomes. The package is intended for clinical research and educational use, notably for the American College of Surgeons.</description>
<author>alba@wustl.edu</author>      <pubDate>Thu, 30 Apr 2026 13:52:38 GMT</pubDate>
    </item>    <item>
      <title>0.1.2</title>
      <link>https://pypi.org/project/clinicalplan/0.1.2/</link>
      <description>ClinicalPLAN is a Python package for predicting postoperative risks from clinical notes using language models. It provides training and inference workflows for fine-tuned models, semi-supervised methods, and multi-task prediction of multiple clinical outcomes. The package is intended for clinical research and educational use, notably for the American College of Surgeons.</description>
<author>alba@wustl.edu</author>      <pubDate>Thu, 30 Apr 2026 13:05:49 GMT</pubDate>
    </item>    <item>
      <title>0.1.1</title>
      <link>https://pypi.org/project/clinicalplan/0.1.1/</link>
      <description>ClinicalPLAN is a Python package for predicting postoperative risks from clinical notes using language models. It provides training and inference workflows for fine-tuned models, semi-supervised methods, and multi-task prediction of multiple clinical outcomes. The package is intended for clinical research and educational use, notably for the American College of Surgeons.</description>
<author>alba@wustl.edu</author>      <pubDate>Thu, 23 Apr 2026 10:54:41 GMT</pubDate>
    </item>    <item>
      <title>0.1.0</title>
      <link>https://pypi.org/project/clinicalplan/0.1.0/</link>
      <description>ClinicalPLAN is a Python package for predicting postoperative risks from clinical notes using language models. It provides training and inference workflows for fine-tuned models, semi-supervised methods, and multi-task prediction of multiple clinical outcomes. The package is intended for clinical research and educational use, notably for the American College of Surgeons.</description>
<author>alba@wustl.edu</author>      <pubDate>Thu, 23 Apr 2026 10:48:16 GMT</pubDate>
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