Development and validation of a machine learning model to predict venous thromboembolism among hospitalized cancer patients

OBJECTIVE: Hospitalized cancer patients are at high risk of venous thromboembolism (VTE). However, no predictive model has been specifically developed for this population. Machine learning (ML) is advantageous for model development. This study was aimed at developing predictive models using three di...

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Detalles Bibliográficos
Autores principales: Meng, Lingqi, Wei, Tao, Fan, Rongrong, Su, Haoze, Liu, Jiahui, Wang, Lijie, Huang, Xinjuan, Qi, Yi, Li, Xuying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583033/
https://www.ncbi.nlm.nih.gov/pubmed/36276886
http://dx.doi.org/10.1016/j.apjon.2022.100128

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9583033/
https://www.ncbi.nlm.nih.gov/pubmed/36276886
http://dx.doi.org/10.1016/j.apjon.2022.100128

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