Cardiovascular heart disease (CHD) is a chief public health
priority worldwide. The 12-Lead Electrocardiogram (ECG) is a
standard procedure in diagnosing CHDs such as Myocardial Infarction
(MI). Nevertheless, due to sparse spatial sampling, it is limited
in identifying cardiac abnormalities. Alternatively, in Body
Surface Cardiac Mapping (BSCM) a higher number of ECGs are
recorded. Hence, BSCM provides a more comprehensive picture of
electrocardiographic information than is possible with the 12-lead
ECG. This work has two main objectives. Firstly, to develop a
classification framework for an accurate and early diagnosis of
acute MI. This decision support system encompasses computational
neural models with the input space based on BSCM. Secondly, since
MI is localised on the torso surface, and due to the high number of
electrocardiographic leads involved in BSCM, it is desirable to
find an optimal reduced lead set for acute MI detection. By
building an additional layer of knowledge between the cardiologist
and clinical practice, this work not only enhances final MI
classification performance but, allow the discovery of new
electrocardiographic MI markers.
General
| Imprint: |
VDM Verlag
|
| Country of origin: |
Germany |
| Release date: |
June 2009 |
| First published: |
June 2009 |
| Authors: |
Jesus Lopez
|
| Dimensions: |
229 x 152 x 12mm (L x W x T) |
| Format: |
Paperback - Trade
|
| Pages: |
204 |
| ISBN-13: |
978-3-639-16579-1 |
| Categories: |
Books >
Medicine >
Clinical & internal medicine >
General
Promotions
|
| LSN: |
3-639-16579-9 |
| Barcode: |
9783639165791 |
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