Application of Machine Learning to the Prediction of Cancer-Associated Venous Thromboembolism

Venous thromboembolism (VTE) is a common and impactful complication of cancer. Several clinical prediction rules have been devised to estimate the risk of a thrombotic event in this patient population, however they are associated with limitations. We aimed to develop a predictive model of cancer-ass...

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Detalles Bibliográficos
Autores principales: Mantha, Simon, Chatterjee, Subrata, Singh, Rohan, Cadley, John, Poon, Chester, Chatterjee, Avijit, Kelly, Daniel, Sterpi, Michelle, Soff, Gerald, Zwicker, Jeffrey, Soria, José, Ruiz, Magdalena, Muñoz, Andres, Arcila, Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10197737/
https://www.ncbi.nlm.nih.gov/pubmed/37214902
http://dx.doi.org/10.21203/rs.3.rs-2870367/v1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10197737/
https://www.ncbi.nlm.nih.gov/pubmed/37214902
http://dx.doi.org/10.21203/rs.3.rs-2870367/v1

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