<?xml version='1.0' encoding='utf-8'?>
<?xml-stylesheet type="text/xsl" href="/v2/static/oai2.xsl"?>
<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd">
  <responseDate>2026-10-09T00:47:18Z</responseDate>
  <request identifier="oai:figshare.com:article/34048754" metadataPrefix="oai_dc" verb="GetRecord">https://api.figshare.com/v2/oai</request>
  <GetRecord>
    <record>
      <header>
        <identifier>oai:figshare.com:article/34048754</identifier>
        <datestamp>2026-10-01T17:36:29Z</datestamp>
        <setSpec>category_1</setSpec>
        <setSpec>category_13</setSpec>
        <setSpec>category_21</setSpec>
        <setSpec>category_734</setSpec>
        <setSpec>category_931</setSpec>
        <setSpec>category_811</setSpec>
        <setSpec>category_69</setSpec>
        <setSpec>category_128</setSpec>
        <setSpec>portal_5</setSpec>
        <setSpec>item_type_1</setSpec>
        <setSpec>month_year_10_2026</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>&lt;p&gt;SHAP Feature Importance Analysis Across All Temporal Horizons for eICU-CRD Mortality Prediction.&lt;/p&gt;</dc:title>
          <dc:creator>Ali Namvar (9279350)</dc:creator>
          <dc:creator>Sundaresh Ram (10428439)</dc:creator>
          <dc:creator>Wassim W. Labaki (10704446)</dc:creator>
          <dc:creator>Stefanie Galban (10428445)</dc:creator>
          <dc:creator>Njira L. Lugogo (13119569)</dc:creator>
          <dc:creator>Craig J. Galban (10428469)</dc:creator>
          <dc:subject>Biophysics</dc:subject>
          <dc:subject>Genetics</dc:subject>
          <dc:subject>Biotechnology</dc:subject>
          <dc:subject>Biological Sciences not elsewhere classified</dc:subject>
          <dc:subject>Information Systems not elsewhere classified</dc:subject>
          <dc:subject>Mathematical Sciences not elsewhere classified</dc:subject>
          <dc:subject>Inorganic Chemistry</dc:subject>
          <dc:subject>Hematology</dc:subject>
          <dc:subject>track physiological instability</dc:subject>
          <dc:subject>support clinical assessment</dc:subject>
          <dc:subject>provide limited insight</dc:subject>
          <dc:subject>multidimensional physiological space</dc:subject>
          <dc:subject>monitoring systems face</dc:subject>
          <dc:subject>method &amp;# 8217</dc:subject>
          <dc:subject>existing approaches rely</dc:subject>
          <dc:subject>distinct clinical signatures</dc:subject>
          <dc:subject>applies geometric analysis</dc:subject>
          <dc:subject>6 %, 16</dc:subject>
          <dc:subject>movement toward higher</dc:subject>
          <dc:subject>state trajectory representation</dc:subject>
          <dc:subject>physiological state monitoring</dc:subject>
          <dc:subject>linking state dynamics</dc:subject>
          <dc:subject>derived physiological states</dc:subject>
          <dc:subject>aware monitoring ),</dc:subject>
          <dc:subject>mortality prediction achieved</dc:subject>
          <dc:subject>evaluated stream using</dc:subject>
          <dc:subject>fold higher mortality</dc:subject>
          <dc:subject>icu stay within</dc:subject>
          <dc:subject>expected calibration error</dc:subject>
          <dc:subject>routine icu data</dc:subject>
          <dc:subject>fold higher</dc:subject>
          <dc:subject>expected state</dc:subject>
          <dc:subject>icu mortality</dc:subject>
          <dc:subject>state outliers</dc:subject>
          <dc:subject>risk states</dc:subject>
          <dc:subject>respectively ),</dc:subject>
          <dc:subject>remained within</dc:subject>
          <dc:subject>outcome prediction</dc:subject>
          <dc:subject>nearest state</dc:subject>
          <dc:subject>assigned states</dc:subject>
          <dc:subject>vital signs</dc:subject>
          <dc:subject>strong discrimination</dc:subject>
          <dc:subject>static thresholds</dc:subject>
          <dc:subject>spent less</dc:subject>
          <dc:subject>severity scores</dc:subject>
          <dc:subject>laboratory values</dc:subject>
          <dc:subject>interpretable patterns</dc:subject>
          <dc:subject>external validation</dc:subject>
          <dc:subject>excellent calibration</dc:subject>
          <dc:subject>driven framework</dc:subject>
          <dc:subject>discover data</dc:subject>
          <dc:subject>developed stream</dc:subject>
          <dc:subject>critical gap</dc:subject>
          <dc:subject>8 hours</dc:subject>
          <dc:subject>72 hours</dc:subject>
          <dc:subject>002 ).</dc:subject>
          <dc:description>&lt;p&gt;(A) 8-hour model, (B) 24-hour model, (C) 48-hour model, (D) 72-hour model, and (E) Full ICU stay model. Violin plots display SHAP value distributions for the top 15 features at each prediction horizon, where values to the right increase predicted mortality and values to the left decrease risk; color indicates underlying feature value (blue = low, pink = high).&lt;/p&gt; &lt;p&gt;(TIF)&lt;/p&gt;</dc:description>
          <dc:date>2026-10-01T17:36:17Z</dc:date>
          <dc:type>Image</dc:type>
          <dc:type>Figure</dc:type>
          <dc:identifier>10.1371/journal.pdig.0001753.s009</dc:identifier>
          <dc:relation>https://figshare.com/articles/figure/_p_SHAP_Feature_Importance_Analysis_Across_All_Temporal_Horizons_for_eICU-CRD_Mortality_Prediction_p_/34048754</dc:relation>
          <dc:rights>CC BY 4.0</dc:rights>
        </oai_dc:dc>
      </metadata>
    </record>
  </GetRecord>
</OAI-PMH>
