Non-invasive prediction for pathologic complete response to neoadjuvant chemoimmunotherapy in lung cancer using CT-based deep learning: a multicenter study

Non-invasive prediction for pathologic complete response to neoadjuvant chemoimmunotherapy in lung cancer using CT-based deep learning: a multicenter study

Neoadjuvant chemoimmunotherapy has revolutionized the therapeutic strategy for non-small cell lung cancer (NSCLC), and identifying candidates likely responding to this advanced treatment is of important clinical significance. The current multi-institutional study aims to develop a deep learning mode...

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Bibliographic Details
Main Authors: Wendong Qu, Cheng Chen, Chuang Cai, Ming Gong, Qian Luo, Yongxiang Song, Minglei Yang, Min Shi
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-03-01
Series:Frontiers in Immunology
Subjects:
deep learning
neoadjuvant chemoimmunotherapy
pathologic complete response
lung cancer
radiomics
Online Access:https://www.frontiersin.org/articles/10.3389/fimmu.2024.1327779/full

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https://www.frontiersin.org/articles/10.3389/fimmu.2024.1327779/full

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