Machine-learned models using hematological inflammation markers in the prediction of short-term acute coronary syndrome outcomes

BACKGROUND: Increased systemic and local inflammation play a vital role in the pathophysiology of acute coronary syndrome. This study aimed to assess the usefulness of selected machine learning methods and hematological markers of inflammation in predicting short-term outcomes of acute coronary synd...

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Detalles Bibliográficos
Autores principales: Pieszko, Konrad, Hiczkiewicz, Jarosław, Budzianowski, Paweł, Rzeźniczak, Janusz, Budzianowski, Jan, Błaszczyński, Jerzy, Słowiński, Roman, Burchardt, Paweł
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6276170/
https://www.ncbi.nlm.nih.gov/pubmed/30509300
http://dx.doi.org/10.1186/s12967-018-1702-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6276170/
https://www.ncbi.nlm.nih.gov/pubmed/30509300
http://dx.doi.org/10.1186/s12967-018-1702-5

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