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Comparative assessment of the capability of machine learning-based radiomic models for predicting omental metastasis in locally advanced gastric cancer

Abstract The study aims to investigate the predictive capability of machine learning algorithms for omental metastasis in locally advanced gastric cancer (LAGC) and to compare the performance metrics of various machine learning predictive models. A retrospective collection of 478 pathologically conf...

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Autori principali: Ahao Wu, Lianghua Luo, Qingwen Zeng, Changlei Wu, Xufeng Shu, Pang Huang, Zhonghao Wang, Tengcheng Hu, Zongfeng Feng, Yi Tu, Yanyan Zhu, Yi Cao, Zhengrong Li
Natura: Artigo
Lingua:Inglês
Pubblicazione: Nature Portfolio 2024-07-01
Serie:Scientific Reports
Soggetti:
Machine learning
Omental metastases
Radiomics
Locally advanced gastric cancer
Positive predictive value
Accesso online:https://doi.org/10.1038/s41598-024-66979-x
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