A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data

BACKGROUND: Heart failure is one of the leading causes of hospitalization in the United States. Advances in big data solutions allow for storage, management, and mining of large volumes of structured and semi-structured data, such as complex healthcare data. Applying these advances to complex health...

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Detalles Bibliográficos
Autores principales: Golas, Sara Bersche, Shibahara, Takuma, Agboola, Stephen, Otaki, Hiroko, Sato, Jumpei, Nakae, Tatsuya, Hisamitsu, Toru, Kojima, Go, Felsted, Jennifer, Kakarmath, Sujay, Kvedar, Joseph, Jethwani, Kamal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6013959/
https://www.ncbi.nlm.nih.gov/pubmed/29929496
http://dx.doi.org/10.1186/s12911-018-0620-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6013959/
https://www.ncbi.nlm.nih.gov/pubmed/29929496
http://dx.doi.org/10.1186/s12911-018-0620-z

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