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...

Full description

Saved in:
Bibliographic Details
Published in:Cancer Vol. 131; no. 11; p. e35883
Main Author: Nierengarten, Mary Beth
Format: Journal Article
Language:English
Published: United States Wiley Subscription Services, Inc 01.06.2025
Subjects:
ISSN:0008-543X, 1097-0142, 1097-0142
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
Bibliography: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