A Machine-Learning Approach to Developing a Predictive Signature Based on Transcriptome Profiling of Ground-Glass Opacities for Accurate Classification and Exploring the Immune Microenvironment of Early-Stage LUAD

Screening for early-stage lung cancer with low-dose computed tomography is recommended for high-risk populations; consequently, the incidence of pure ground-glass opacity (pGGO) is increasing. Ground-glass opacity (GGO) is considered the appearance of early lung cancer, and there remains an unmet cl...

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Detalles Bibliográficos
Autores principales: Zhao, Zhenyu, Yin, Wei, Peng, Xiong, Cai, Qidong, He, Boxue, Shi, Shuai, Peng, Weilin, Tu, Guangxu, Li, Yunping, Li, Dateng, Tao, Yongguang, Peng, Muyun, Wang, Xiang, Yu, Fenglei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Immunology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9178173/
https://www.ncbi.nlm.nih.gov/pubmed/35693786
http://dx.doi.org/10.3389/fimmu.2022.872387

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9178173/
https://www.ncbi.nlm.nih.gov/pubmed/35693786
http://dx.doi.org/10.3389/fimmu.2022.872387

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