PhysioMiner : a scalable cloud based framework for physiological waveform mining
Name
894116037-MIT.pdf
Description
Full printable version
Size
10.61 MB
Format
Adobe PDF
Checksum (MD5)
d6f86275dd578c020e6d4a58232f1454
Author(s)
Gopal, Vineet
Advisor(s)
Kalyan Veeramachaneni and Una-May O'Reilly.
Alternative Title
Scalable cloud based framework for physiological waveform mining
Date Issued
2014
Publisher
Massachusetts Institute of Technology
Abstract
This work presents PhysioMiner, a large scale machine learning and analytics framework for physiological waveform mining. It is a scalable and flexible solution for researchers and practitioners to build predictive models from physiological time series data. It allows users to specify arbitrary features and conditions to train the model, computing everything in parallel in the cloud. PhysioMiner is tested on a large dataset of electrocardiography (ECG) from 6000 patients in the MIMIC database. Signals are cleaned and processed, and features are extracted per period. A total of 1.2 billion heart beats were processed and 26 billion features were extracted resulting in half a terabyte database. These features were aggregated for windows corresponding to patient events. These aggregated features were fed into DELPHI, a multi algorithm multi parameter cloud based system to build a predictive model. An area under the curve of 0.693 was achieved for an acute hypotensive event prediction from the ECG waveform alone. The results demonstrate the scalability and flexibility of PhysioMiner on real world data. PhysioMiner will be an important tool for researchers to spend less time building systems, and more time building predictive models.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
Thesis: S.B., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 69-70).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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