Predicting radiation pneumonitis in lung cancer using machine learning and multimodal features: a systematic review and meta-analysis of diagnostic accuracy

Predicting radiation pneumonitis in lung cancer using machine learning and multimodal features: a systematic review and meta-analysis of diagnostic accuracy

Abstract Objectives To evaluate the diagnostic accuracy of machine learning models incorporating multimodal features for predicting radiation pneumonitis in lung cancer through a systematic review and meta-analysis. Methods Relevant studies were identified through a systematic search of PubMed, Web...

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Bibliographic Details
Main Authors: Zhi Chen, GuangMing Yi, XinYan Li, Bo Yi, XiaoHui Bao, Yin Zhang, XiaoYue Zhang, ZhenZhou Yang, Zhengjun Guo
Format: Article
Language:English
Published: BMC 2024-11-01
Series:BMC Cancer
Subjects:
Lung cancer
Multiomics
Machine learning
Artificial intelligence
Radiomics
Radiation pneumonitis
Online Access:https://doi.org/10.1186/s12885-024-13098-5
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https://doi.org/10.1186/s12885-024-13098-5

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