Machine Learning–Based Prognostic Model for Patients After Lung Transplantation

IMPORTANCE: Although numerous prognostic factors have been found for patients after lung transplantation (LTx) over the years, an accurate prognostic tool for LTx recipients remains unavailable. OBJECTIVE: To develop and validate a prognostic model for predicting overall survival in patients after L...

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Detalles Bibliográficos
Autores principales: Tian, Dong, Yan, Hao-Ji, Huang, Heng, Zuo, Yu-Jie, Liu, Ming-Zhao, Zhao, Jin, Wu, Bo, Shi, Ling-Zhi, Chen, Jing-Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2023
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163387/
https://www.ncbi.nlm.nih.gov/pubmed/37145595
http://dx.doi.org/10.1001/jamanetworkopen.2023.12022

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163387/
https://www.ncbi.nlm.nih.gov/pubmed/37145595
http://dx.doi.org/10.1001/jamanetworkopen.2023.12022

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