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Prognostic and predictive value of the newly proposed grading system of invasive pulmonary adenocarcinoma in Chinese patients: a retrospective multicohort study.
Hou L, Wang T, Chen D, She Y, Deng J, Yang M, Zhang Y, Zhao M, Zhong Y, Ma M, Zhao G, Chen Y, Xie D, Zhu Y, Chen Q, Wu C, Chen C; Multi-omics Classifier for Pulmonary Nodules (MISSION) Collaborative Group. Hou L, et al. Mod Pathol. 2022 Jun;35(6):749-756. doi: 10.1038/s41379-021-00994-5. Epub 2022 Jan 10. Mod Pathol. 2022. PMID: 35013526 Free article.
Implementation of artificial intelligence in the histological assessment of pulmonary subsolid nodules.
Deng J, Zhao M, Li Q, Zhang Y, Ma M, Li C, Wang J, She Y, Jiang Y, Zhang Y, Wang T, Wu C, Hou L, Zhong S, Jin S, Qian D, Xie D, Zhu Y, Tandon YK, Snoeckx A, Jin F, Yu B, Zhao G, Chen C. Deng J, et al. Among authors: yu b. Transl Lung Cancer Res. 2021 Dec;10(12):4574-4586. doi: 10.21037/tlcr-21-971. Transl Lung Cancer Res. 2021. PMID: 35070762 Free PMC article.
PET/CT-based deep learning grading signature to optimize surgical decisions for clinical stage I invasive lung adenocarcinoma and biologic basis under its prediction: a multicenter study.
Zhong Y, Cai C, Chen T, Gui H, Chen C, Deng J, Yang M, Yu B, Song Y, Wang T, Chen Y, Shi H, Xie D, Chen C, She Y. Zhong Y, et al. Among authors: yu b. Eur J Nucl Med Mol Imaging. 2024 Jan;51(2):521-534. doi: 10.1007/s00259-023-06434-7. Epub 2023 Sep 19. Eur J Nucl Med Mol Imaging. 2024. PMID: 37725128
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