OWL: an optimized and independently validated machine learning prediction model for lung cancer screening based on the UK Biobank, PLCO, and NLST populations

BACKGROUND: A reliable risk prediction model is critically important for identifying individuals with high risk of developing lung cancer as candidates for low-dose chest computed tomography (LDCT) screening. Leveraging a cutting-edge machine learning technique that accommodates a wide list of quest...

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Detalles Bibliográficos
Autores principales: Pan, Zoucheng, Zhang, Ruyang, Shen, Sipeng, Lin, Yunzhi, Zhang, Longyao, Wang, Xiang, Ye, Qian, Wang, Xuan, Chen, Jiajin, Zhao, Yang, Christiani, David C., Li, Yi, Chen, Feng, Wei, Yongyue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9881220/
https://www.ncbi.nlm.nih.gov/pubmed/36701900
http://dx.doi.org/10.1016/j.ebiom.2023.104443

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9881220/
https://www.ncbi.nlm.nih.gov/pubmed/36701900
http://dx.doi.org/10.1016/j.ebiom.2023.104443

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