Corrigendum: Differentiation of early-stage tumors from benign lesions manifesting as pure ground-glass nodule: a clinical prediction study based on AI-derived quantitative parameters

Shuxiang Chen; Huijuan Zhang; Yifan Chen; Shuo Chen; Wenfu Cao; Yongxiu Tong

PMC · DOI:10.3389/fonc.2025.1631465·June 3, 2025

Corrigendum: Differentiation of early-stage tumors from benign lesions manifesting as pure ground-glass nodule: a clinical prediction study based on AI-derived quantitative parameters

Shuxiang Chen, Huijuan Zhang, Yifan Chen, Shuo Chen, Wenfu Cao, Yongxiu Tong

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Abstract

Linked entities

Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.

Diseases2

tumors benign lesions

Keywords

lungpure ground-glass noduleidentificationnomogramCTAIquantitative parametersbenignity

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TopicsRadiomics and Machine Learning in Medical Imaging

Full text

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It should be “5. Wan YL, Wu PW, Huang PC, Tsay PK, Pan KT, Trang NN, et al. The use of artificial intelligence in the differentiation of malignant and benign lung nodules on computed tomograms proven by surgical pathology. Cancers (Basel). (2020) 12:2211. doi: 10.3390/cancers12082211.

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The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.