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Using machine learning on cardiorespiratory fitness data for predicting hypertension: The Henry Ford ExercIse Testing (FIT) Project
This study evaluates and compares the performance of different machine learning techniques on predicting the individuals at risk of developing hypertension, and who are likely to benefit most from interventions, using the cardiorespiratory fitness data. The dataset of this study contains information...
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| Veröffentlicht in: | PLoS One |
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| Hauptverfasser: | , , , , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Public Library of Science
2018
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5905952/ https://ncbi.nlm.nih.gov/pubmed/29668729 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0195344 |
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