Deep learning model for predicting immunotherapy response in patients with advanced NSCLC Study findings demonstrate a strong and independent deep learning‐based feature associated with an immune checkpoint inhibitor response in patients with NSCLC across cohorts
This news section offers Cancer readers timely information on events, public policy analysis, topical issues, and personalities. In this issue, study findings demonstrate a strong and independent deep learning‐based feature associated with an immune checkpoint inhibitor response in patients with NSC...
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| Veröffentlicht in: | Cancer Jg. 131; H. 11; S. e35883 |
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| 1. Verfasser: | |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
United States
Wiley Subscription Services, Inc
01.06.2025
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| Schlagworte: | |
| ISSN: | 0008-543X, 1097-0142, 1097-0142 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | This news section offers Cancer readers timely information on events, public policy analysis, topical issues, and personalities. In this issue, study findings demonstrate a strong and independent deep learning‐based feature associated with an immune checkpoint inhibitor response in patients with NSCLC across cohorts. In addition, cabozantinib was found to significantly improve progression‐free survival in a heavily pretreated population of patients with advanced neuroendocrine tumors, and a new standard of care is discussed for patients with asymptomatic brain metastases from melanoma. |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 ObjectType-News-1 |
| ISSN: | 0008-543X 1097-0142 1097-0142 |
| DOI: | 10.1002/cncr.35883 |