Assisted auscultation : creation and visualization of high dimensional feature spaces for the detection of mitral regurgitation
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, June 2006.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2007
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| Online Access: | http://hdl.handle.net/1721.1/36806 |
| _version_ | 1826193865578643456 |
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| author | Leeds, Daniel Demeny |
| author2 | John V. Guttag. |
| author_facet | John V. Guttag. Leeds, Daniel Demeny |
| author_sort | Leeds, Daniel Demeny |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, June 2006. |
| first_indexed | 2024-09-23T09:46:32Z |
| format | Thesis |
| id | mit-1721.1/36806 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T09:46:32Z |
| publishDate | 2007 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/368062019-04-10T09:05:28Z Assisted auscultation : creation and visualization of high dimensional feature spaces for the detection of mitral regurgitation Leeds, Daniel Demeny John V. Guttag. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, June 2006. "May 2006." Includes bibliographical references (p. 83-84). Cardiac auscultation, listening to the heart using a stethoscope, often constitutes the first step in detection of common heart problems. Unfortunately, primary care physicians, who perform this initial screening, often lack the experience to correctly evaluate what they hear. False referrals are frequent, costing hundreds of dollars and hours of time for many patients. We report on a system we have built to aid medical practitioners in diagnosing Mitral Regurgitation (MR) based on heart sounds. Our work builds on the "prototypical beat" introduced by Syed in [17] to extract two different feature sets characterizing systolic acoustic activity. One feature set is derived from current medical knowledge. The other is based on unsupervised learning of systolic shapes, using component Analysis. Our system employs self-organizing maps (SOMs) to depict the distribution of patients in each feature space as labels within a two-dimensional colored grid. A user screens new patients by viewing their projections onto the SOM, and determining whether they are closer in space, and thus more similar, to patients with or without MR. We evaluated our system on 46 patients. Using a combination of the two feature sets, SOM-based diagnosis classified patients with accuracy similar to that of a cardiologist. by Daniel Demeny Leeds. M.Eng. 2007-03-12T17:55:29Z 2007-03-12T17:55:29Z 2006 Thesis http://hdl.handle.net/1721.1/36806 80768708 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 83 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Leeds, Daniel Demeny Assisted auscultation : creation and visualization of high dimensional feature spaces for the detection of mitral regurgitation |
| title | Assisted auscultation : creation and visualization of high dimensional feature spaces for the detection of mitral regurgitation |
| title_full | Assisted auscultation : creation and visualization of high dimensional feature spaces for the detection of mitral regurgitation |
| title_fullStr | Assisted auscultation : creation and visualization of high dimensional feature spaces for the detection of mitral regurgitation |
| title_full_unstemmed | Assisted auscultation : creation and visualization of high dimensional feature spaces for the detection of mitral regurgitation |
| title_short | Assisted auscultation : creation and visualization of high dimensional feature spaces for the detection of mitral regurgitation |
| title_sort | assisted auscultation creation and visualization of high dimensional feature spaces for the detection of mitral regurgitation |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/36806 |
| work_keys_str_mv | AT leedsdanieldemeny assistedauscultationcreationandvisualizationofhighdimensionalfeaturespacesforthedetectionofmitralregurgitation |