2012 AnIntegratedDataMiningApproacht

• (Mao et al., 2012) ⇒ Yi Mao, Wenlin Chen, Yixin Chen, Chenyang Lu, Marin Kollef, and Thomas Bailey. (2012). “An Integrated Data Mining Approach to Real-time Clinical Monitoring and Deterioration Warning.” In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2012). ISBN:978-1-4503-1462-6 doi:10.1145/2339530.2339709

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222012%22+An+Integrated+Data+Mining+Approach+to+Real-time+Clinical+Monitoring+and+Deterioration+Warning
• http://dl.acm.org/citation.cfm?id=2339530.2339709&preflayout=flat#citedby

Quotes

Author Keywords

• Data mining; deterioration warning; feature selection; real-time clinical monitoring; time-series classification

Abstract

Clinical study found that early detection and intervention are essential for preventing clinical deterioration in patients, for patients both in intensive care units (ICU) as well as in general wards but under real-time data sensing (RDS). In this paper, we develop an integrated data mining approach to give early deterioration warnings for patients under real-time monitoring in ICU and RDS.

Existing work on mining real-time clinical data often focus on certain single vital sign and specific disease. In this paper, we consider an integrated data mining approach for general sudden deterioration warning. We synthesize a large feature set that includes first and second order time-series features, detrended fluctuation analysis (DFA), spectral analysis, approximative entropy, and cross-signal features. We then systematically apply and evaluate a series of established data mining methods, including forward feature selection, linear and nonlinear classification algorithms, and exploratory undersampling for class imbalance.

An extensive empirical study is conducted on real patient data collected between 2001 and 2008 from a variety of ICUs. Results show the benefit of each of the proposed techniques, and the final integrated approach significantly improves the prediction quality. The proposed clinical warning system is currently under integration with the electronic medical record system at B arnes-Jewish Hospital in preparation for a clinical trial. This work represents a promising step toward general early clinical warning which has the potential to significantly improve the quality of patient care in hospitals.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2012 AnIntegratedDataMiningApproacht	Yixin Chen Yi Mao Wenlin Chen Chenyang Lu Marin Kollef Thomas Bailey			An Integrated Data Mining Approach to Real-time Clinical Monitoring and Deterioration Warning				10.1145/2339530.2339709		2012