Evaluating parameter optimization in locality-sensitive hashing for high-dimensional physiological waveforms
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2019
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| Online Access: | http://hdl.handle.net/1721.1/120650 |
| _version_ | 1826195556435755008 |
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| author | Chakradhar, Vineel A |
| author2 | Erik Hemberg. |
| author_facet | Erik Hemberg. Chakradhar, Vineel A |
| author_sort | Chakradhar, Vineel A |
| collection | MIT |
| description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018. |
| first_indexed | 2024-09-23T10:14:35Z |
| format | Thesis |
| id | mit-1721.1/120650 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T10:14:35Z |
| publishDate | 2019 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1206502019-04-12T20:33:37Z Evaluating parameter optimization in locality-sensitive hashing for high-dimensional physiological waveforms Chakradhar, Vineel A Erik Hemberg. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018. Cataloged from PDF version of thesis. "The pagination listed in the Table of Contents does not correlate with actual page numbering"--Disclaimer Notice page. Includes bibliographical references (pages 71-72). We develop and evaluate a theoretical architecture to inform parameter choice for locality-sensitive hashing methods used towards identifying similarity in physiological waveform time-series data. The goal is to achieve increased probability of successful patient outcomes in emergency rooms by tackling the problem of efficient information retrieval within massive, high-dimensional medical datasets. To solve this problem, we explore the relationship between a number of data inputs and elements of locality-sensitive hashing schemes in order to drive optimal choice of parameters throughout the pipeline from raw data to locality-sensitive hashing output. We achieve significant increases in retrieval times while generally maintaining the prediction accuracy achieved by naive retrieval methodologies. by Vineel A. Chakradhar. M. Eng. 2019-03-01T19:55:10Z 2019-03-01T19:55:10Z 2018 2018 Thesis http://hdl.handle.net/1721.1/120650 1088411546 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 72 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Chakradhar, Vineel A Evaluating parameter optimization in locality-sensitive hashing for high-dimensional physiological waveforms |
| title | Evaluating parameter optimization in locality-sensitive hashing for high-dimensional physiological waveforms |
| title_full | Evaluating parameter optimization in locality-sensitive hashing for high-dimensional physiological waveforms |
| title_fullStr | Evaluating parameter optimization in locality-sensitive hashing for high-dimensional physiological waveforms |
| title_full_unstemmed | Evaluating parameter optimization in locality-sensitive hashing for high-dimensional physiological waveforms |
| title_short | Evaluating parameter optimization in locality-sensitive hashing for high-dimensional physiological waveforms |
| title_sort | evaluating parameter optimization in locality sensitive hashing for high dimensional physiological waveforms |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/120650 |
| work_keys_str_mv | AT chakradharvineela evaluatingparameteroptimizationinlocalitysensitivehashingforhighdimensionalphysiologicalwaveforms |