| Autor: |
C. K. Roopa, B.S. Harish |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
International Journal of Interactive Multimedia and Artificial Intelligence, Vol 6, Iss 1, Pp 16-25 (2020) |
| Druh dokumentu: |
article |
| ISSN: |
1989-1660 |
| DOI: |
10.9781/ijimai.2019.02.001 |
| Popis: |
Cardio-vascular diseases are one of the foremost causes of mortality in today’s world. The prognosis for cardiovascular diseases is usually done by ECG signal, which is a simple 12-lead Electrocardiogram (ECG) that gives complete information about the function of the heart including the amplitude and time interval of P-QRST-U segment. This article recommends a novel approach to identify the location of thrombus in culprit artery using the Information Fuzzy Network (IFN). Information Fuzzy Network, being a supervised machine learning technique, takes known evidences based on rules to create a predicted classification model with thrombus location obtained from the vast input ECG data. These rules are well-defined procedures for selecting hypothesis that best fits a set of observations. Results illustrate that the recommended approach yields an accurateness of 92.30%. This novel approach is shown to be a viable ECG analysis approach for identifying the culprit artery and thus localizing the thrombus. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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