2013 IEEE International Conference on Big Data 2013
DOI: 10.1109/bigdata.2013.6691760
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Big data solutions for predicting risk-of-readmission for congestive heart failure patients

Abstract: Mitigating risk-of-readmission of Congestive Heart Failure (CHF) patients within 30 days of discharge is important because such readmissions are not only expensive but also critical indicator of provider care and quality of treatment. Accurately predicting the risk-of-readmission may allow hospitals to identify high-risk patients and eventually improve quality of care by identifying factors that contribute to such readmissions in many scenarios. In this paper, we investigate the problem of predicting risk-of-r… Show more

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Cited by 78 publications
(64 citation statements)
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References 28 publications
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“…Mahout's Random Forest implementation has been applied across many different application domains, but has been used particularly often in healthcare-related studies. It has been used to predict the severity of motor neuron disease [117], identify high risk patients [118], and predict the risk of readmission for congestive heart failure patients [119]. It has also been used as part of a general predictive healthcare analytics framework.…”
Section: Classificationmentioning
confidence: 99%
“…Mahout's Random Forest implementation has been applied across many different application domains, but has been used particularly often in healthcare-related studies. It has been used to predict the severity of motor neuron disease [117], identify high risk patients [118], and predict the risk of readmission for congestive heart failure patients [119]. It has also been used as part of a general predictive healthcare analytics framework.…”
Section: Classificationmentioning
confidence: 99%
“…Kiyana Zolfaghar et al [17] has presented prediction model to give possible solutions for congestive heart failure incidents using Mahout Framework. The raw data is pre-processed and converted to encoded format which will be given as input to the Mahout framework, using random forest algorithm.…”
Section: Iv) Veracitymentioning
confidence: 99%
“…According to Gartner [18], Big data is defined as high-volume, high-velocity and high-variety information assets that demand costeffective, innovative forms of information processing for enhanced insight and decision making. The three V"s of Big Data are -Volume, Velocity, and Variety.…”
Section: Big Data and Its Characteristicsmentioning
confidence: 99%