Machine Learning to Predict the Likelihood of Acute Myocardial Infarction

Variations in cardiac troponin concentrations by age, sex, and time between samples in patients with suspected myocardial infarction are not currently accounted for in diagnostic approaches. We aimed to combine these variables through machine learning to improve the assessment of risk for individual...

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Detalles Bibliográficos
Autores principales: Than, Martin P., Pickering, John W., Sandoval, Yader, Shah, Anoop S.V., Tsanas, Athanasios, Apple, Fred S., Blankenberg, Stefan, Cullen, Louise, Mueller, Christian, Neumann, Johannes T., Twerenbold, Raphael, Westermann, Dirk, Beshiri, Agim, Mills, Nicholas L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2019
Materias:
Original Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749969/
https://www.ncbi.nlm.nih.gov/pubmed/31416346
http://dx.doi.org/10.1161/CIRCULATIONAHA.119.041980

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749969/
https://www.ncbi.nlm.nih.gov/pubmed/31416346
http://dx.doi.org/10.1161/CIRCULATIONAHA.119.041980

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