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Development meaningful feature set for electrocardiogram waveform analysis using unsupervised deep learning algorithms
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 윤, 덕용 | - |
| dc.contributor.author | 장, 종환 | - |
| dc.date.accessioned | 2021-11-10T05:51:56Z | - |
| dc.date.available | 2021-11-10T05:51:56Z | - |
| dc.date.issued | 2021 | - |
| dc.identifier.uri | http://repository.ajou.ac.kr/handle/201003/19774 | - |
| dc.description.abstract | 비공개 | - |
| dc.description.tableofcontents | I. Introduction 1
A. Background 1 1. Electrocardiogram analysis 1 (A) Electrocardiogram 1 (B) Previous ECG analysis methods 2 (C) Deep learning approach for ECG analysis 10 B. Purpose of this study 13 II. Methods 14 A. Data resource 17 1. Ajou university medical center 18 2. Shaoxing hospital 19 3. BIH-MIT 21 B. Model 23 1. Unsupervised learning 23 2. Autoencoder 24 (A) Autoencocder structure in our study 27 3. Variational autoencoder 42 C. Evaluation 45 1. Model evaluation 45 (A) Autoencocder 45 (B) Variational Autoencocder 45 2. Evaluation of features 46 (A) Anomaly detection 47 (B) Clustering 49 (C) Transfer learning 53 (D) Latent space exploration 58 III. Results 59 A. Data resource 59 B. Autoencoder 61 1. Reconstruction performance 61 2. Clustering 62 3. Transfer learning 65 C. Variational autoencoder 70 1. Reconstruction performance 70 2. Clustering 72 3. Transfer learning 75 4. Anomaly detection 82 5. Latent space exploration 85 IV Discussion 87 V. Conclusion 93 VI. References 94 | - |
| dc.language.iso | en | - |
| dc.title | Development meaningful feature set for electrocardiogram waveform analysis using unsupervised deep learning algorithms | - |
| dc.type | Thesis | - |
| dc.identifier.url | http://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000030708 | - |
| dc.description.degree | Doctor | - |
| dc.contributor.department | 대학원 의학과 | - |
| dc.contributor.affiliatedAuthor | 장, 종환 | - |
| dc.date.awarded | 2021 | - |
| dc.type.local | Theses | - |
| dc.citation.date | 2021 | - |
| dc.embargo.liftdate | 9999-12-31 | - |
| dc.embargo.terms | 9999-12-31 | - |
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