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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...
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. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2019
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Materias: | |
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 |
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