The purpose of this study is the evaluation of the web cloud-based analytic service IBM Watson Analytics as a tool for the management of Congestive Heart Failure (CHF). In particular, we want to assess if this service is suitable for the identification of physiological parameters able to predict outputs of interest such as disease severity, among a set of various physiological parameters and the realization of a predictive model. Using IBM Watson Analytics, we analyzed a database consisting of 250 records containing physiological parameters from 250 patients suffering from Congestive Heart Failure. Among the physiological parameters, we identified the best predictors of 2 outputs of interest (Severity of Congestive Heart Failure and Exacerbation Frequency) and analyzed the relationship between outputs and predictors and between predictors and the other physiological parameters.
机构:
Univ Calif Davis, Dept Internal Med, 4860 Y St Suite 0100, Sacramento, CA 95817 USAUniv Calif Davis, Dept Internal Med, 4860 Y St Suite 0100, Sacramento, CA 95817 USA
Chen, Jennifer
Aronowitz, Paul
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Univ Calif Davis, Dept Internal Med, 4150 V Street Suite 3100 PSSB, Sacramento, CA 95817 USAUniv Calif Davis, Dept Internal Med, 4860 Y St Suite 0100, Sacramento, CA 95817 USA
机构:
Univ Maryland, Med Ctr, Dept Emergency Med, Emergency Med Internal Med Crit Care Program, Baltimore, MD 21201 USA
Univ Maryland, Med Ctr, Dept Med, Baltimore, MD 21201 USAUniv Maryland, Med Ctr, Dept Emergency Med, Emergency Med Internal Med Crit Care Program, Baltimore, MD 21201 USA
Scott, Michael C.
Winters, Michael E.
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Univ Maryland, Med Ctr, Dept Emergency Med, Emergency Med Internal Med Crit Care Program, Baltimore, MD 21201 USAUniv Maryland, Med Ctr, Dept Emergency Med, Emergency Med Internal Med Crit Care Program, Baltimore, MD 21201 USA