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          <dc:title>Supplementary Figure S3 from Utilizing Machine Learning to Identify Multimodal Signatures for Patients Who Would Benefit from the Addition of Tremelimumab to Durvalumab and Chemotherapy (TRIDENT)</dc:title>
          <dc:creator>Ferdinandos Skoulidis (16041866)</dc:creator>
          <dc:creator>Salma K. Jabbour (25153919)</dc:creator>
          <dc:creator>Edward B. Garon (15033509)</dc:creator>
          <dc:creator>Puneeth Iyengar (25153922)</dc:creator>
          <dc:creator>Giorgio Scagliotti (25153925)</dc:creator>
          <dc:creator>Loïc Ferrer (25153928)</dc:creator>
          <dc:creator>Guillaume Etchepare (25153931)</dc:creator>
          <dc:creator>Olivier Gallinato (25153934)</dc:creator>
          <dc:creator>Jérôme Faure (25153937)</dc:creator>
          <dc:creator>Paul Bernard (25153940)</dc:creator>
          <dc:creator>Thierry Colin (25153943)</dc:creator>
          <dc:creator>Philippe Menu (25153946)</dc:creator>
          <dc:creator>Yian Lin (25153949)</dc:creator>
          <dc:creator>Ling Cai (25153952)</dc:creator>
          <dc:creator>Ammar Ahmed Chaudhry (25153955)</dc:creator>
          <dc:creator>Amanda Remorino (25153958)</dc:creator>
          <dc:creator>Ross Stewart (14851015)</dc:creator>
          <dc:creator>Luisa Luciani-Silverman (25153961)</dc:creator>
          <dc:creator>Katy Miller (25153964)</dc:creator>
          <dc:creator>David Dellamonica (25153967)</dc:creator>
          <dc:creator>Jolyon Faria (25153970)</dc:creator>
          <dc:creator>Yiduo Zhang (25153973)</dc:creator>
          <dc:subject>Cancer</dc:subject>
          <dc:subject>Cancer Detection and Diagnosis</dc:subject>
          <dc:subject>Immuno-oncology</dc:subject>
          <dc:subject>Biomarkers</dc:subject>
          <dc:subject>Imaging biomarkers</dc:subject>
          <dc:subject>Clinical Imaging</dc:subject>
          <dc:subject>Immunology</dc:subject>
          <dc:subject>Antibodies/immunoconjugates</dc:subject>
          <dc:subject>Immunotherapy</dc:subject>
          <dc:subject>Checkpoint blockade</dc:subject>
          <dc:subject>Lung Cancer</dc:subject>
          <dc:description>&lt;p&gt;Supplementary Figure 3. Partial dependence plots (PDPs) for (A) Model 4, analysis set 2 (clinical and radiomics); (B) Model 7, analysis set 3 (clinical and genomics); (C) Model 19, analysis set 6 (clinical and genomics, non-squamous patients only). The PDPs show the predicted CATE against the selected feature, by averaging the model's predictions over all patients with that feature set to a specific value and all other features held constant. Panel A shows PDPs for the top 5 features in Figure 3A, panel 3. Panel B shows PDPs for the top 5 features in Figure 3B, panel 3. Panel C shows PDPs for the top 5 features in Figure 3C, panel 3.&lt;/p&gt;</dc:description>
          <dc:date>2026-10-01T00:00:00Z</dc:date>
          <dc:type>Text</dc:type>
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          <dc:identifier>10.1158/1078-0432.34040696</dc:identifier>
          <dc:relation>https://figshare.com/articles/journal_contribution/Supplementary_Figure_S3_from_Utilizing_Machine_Learning_to_Identify_Multimodal_Signatures_for_Patients_Who_Would_Benefit_from_the_Addition_of_Tremelimumab_to_Durvalumab_and_Chemotherapy_TRIDENT_/34040696</dc:relation>
          <dc:rights>CC BY</dc:rights>
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