Technical Approach : Time-series preprocessing and feature extraction

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Project Title: Integrated Real-Time Clinical Deterioration Prediction for Hospitalized Patients and Outpatients Technical Approach : •Time-series preprocessing and feature extraction •Nonlinear, interpretable, scalable, and sparse time-series classification algorithms; •Data-driven dynamic sensing reconfiguration schemes; T. Bailey, Y. Chen, Y. Mao, C. Lu, G. Hackmann, S. T. Micek, K. Heard, K. Faulkner, and M. H. Kollef, “A Trial of a Real-time Alert for Clinical Deterioration in Patients Hospitalized on General Medical Wards.” Journal of Hospital Medicine, 8(5):236- 242, 2013. http://www.cse.wustl.edu/~ychen/public/hospital.pdf Motivation: •To develop integrated early warning system alerts for hospitalized patients employing both electronically available data and real-time vital signs data; •To establish predictive algorithms from informational cloud data for outpatients potentially at risk for hospital readmission; Transformative: • New algorithms for predicting clinical deterioration and readmission from noisy and high-dimensional data streams; • A novel alert explanation system which highlights the most relevant factors and suggests possible intervention; • An adaptive sensing reconfiguration scheme for better user experience and energy efficiency; Broader Impacts : • Improved clinical outcomes and potential reduction of both patient mortality rates and healthcare costs; • Widely-disseminated methods and software; • It addresses a major medical, societal, and governmental concern which has the potential to improve the overall administration of healthcare in the United States.

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T. Bailey, Y. Chen, Y. Mao, C. Lu, G. Hackmann, S. T. Micek, K. Heard, K. Faulkner, and M. H. Kollef, “A Trial of a Real-time Alert for Clinical Deterioration in Patients Hospitalized on General Medical Wards.” Journal of Hospital Medicine, 8(5):236-242, 2013. - PowerPoint PPT Presentation

Transcript of Technical Approach : Time-series preprocessing and feature extraction

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Project Title: Integrated Real-Time Clinical Deterioration Prediction for Hospitalized Patients and Outpatients

Technical Approach:•Time-series preprocessing and feature extraction•Nonlinear, interpretable, scalable, and sparse time-series classification algorithms;•Data-driven dynamic sensing reconfiguration schemes;

T. Bailey, Y. Chen, Y. Mao, C. Lu, G. Hackmann, S. T. Micek, K. Heard, K. Faulkner, and M. H. Kollef, “A Trial of a Real-time Alert for Clinical Deterioration in Patients Hospitalized on General Medical Wards.” Journal of Hospital Medicine, 8(5):236-242, 2013.

http://www.cse.wustl.edu/~ychen/public/hospital.pdf

Motivation:•To develop integrated early warning system alerts for hospitalized patients employing both electronically available data and real-time vital signs data;•To establish predictive algorithms from informational cloud data for outpatients potentially at risk for hospital readmission;Transformative:• New algorithms for predicting clinical deterioration and readmission from noisy and high-dimensional data streams;• A novel alert explanation system which highlights the most relevant factors and suggests possible intervention;• An adaptive sensing reconfiguration scheme for better user experience and energy efficiency;

Broader Impacts:• Improved clinical outcomes and potential reduction of both patient mortality rates and healthcare costs;• Widely-disseminated methods and software;• It addresses a major medical, societal, and governmental concern which has the potential to improve the overall administration of healthcare in the United States.