摘要
Heart murmurs are often the important representations of heart valve disorders. But not all murmurs are pathological. For example, musical murmurs are normal in children. In order to reduce healthcare expenditures and unnecessary parental anxieties, this study aims to develop techniques to distinguish musical murmurs from other murmurs most of which are organic. Wavelet transform and t-test are used for feature extraction and selection, respectively. An ensemble classification method is developed from three classification techniques: Discriminant analysis, support vector machine, and artificial neural network. The computational results demonstrate high sensitivity and specificity.
| 原文 | 英語 |
|---|---|
| 出版狀態 | 已出版 - 2010 |
| 對外發佈 | 是 |
| 事件 | IIE Annual Conference and Expo 2010 - Cancun, 墨西哥 持續時間: 05 06 2010 → 09 06 2010 |
Conference
| Conference | IIE Annual Conference and Expo 2010 |
|---|---|
| 國家/地區 | 墨西哥 |
| 城市 | Cancun |
| 期間 | 05/06/10 → 09/06/10 |
指紋
深入研究「Feature extraction and classification of heart murmurs using heart sound」主題。共同形成了獨特的指紋。引用此
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