Deep learning on CT scans to predict checkpoint inhibitor treatment outcomes in advanced melanoma

Deep learning on CT scans to predict checkpoint inhibitor treatment outcomes in advanced melanoma

Abstract Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high costs. Accurate biomarkers for response are lacking. The present work is the first to investigate the value of deep learning on CT imaging of...

Full description

Saved in:
Bibliographic Details
Main Authors: Laurens S. Ter Maat, Rob A. J. De Mooij, Isabella A. J. Van Duin, Joost J. C. Verhoeff, Sjoerd G. Elias, Tim Leiner, Wouter A. C. van Amsterdam, Max F. Troenokarso, Eran R. A. N. Arntz, Franchette W. P. J. Van den Berkmortel, Marye J. Boers-Sonderen, Martijn F. Boomsma, Fons J. M. Van den Eertwegh, Jan Willem de Groot, Geke A. P. Hospers, Djura Piersma, Art Vreugdenhil, Hans M. Westgeest, Ellen Kapiteijn, Ardine A. De Wit, Willeke A. M. Blokx, Paul J. Van Diest, Pim A. De Jong, Josien P. W. Pluim, Karijn P. M. Suijkerbuijk, Mitko Veta
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-024-81188-2
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items