التفاصيل البيبلوغرافية
| العنوان: |
The performance of ECG delineation using the proposed DAE-ConvBiLSTM model. |
| المؤلفون: |
Bambang Tutuko (14312553), Annisa Darmawahyuni (14312556), Siti Nurmaini (14312559), Alexander Edo Tondas (14312562), Muhammad Naufal Rachmatullah (14312565), Samuel Benedict Putra Teguh (14312568), Firdaus Firdaus (8952848), Ade Iriani Sapitri (14312571), Rossi Passarella (14312574) |
| سنة النشر: |
2022 |
| مصطلحات موضوعية: |
Cell Biology, Physiology, Developmental Biology, Cancer, Mental Health, Information Systems not elsewhere classified, widely used diagnostic, bidirectional long short, paper presents end, end learning using, end learning single, end learning algorithm, ecg signal processing, ecg main waveform, conventional denoising techniques, classify ecg waveforms, unsupervised learning dae, supervised learning convbilstm, lead electrocardiogram signal, heart abnormality diagnosis, end diagnosis, heart activities, ecg delineation, denoising auto, denoising algorithms, %22">xlink ">, ventricular repolarisation, term memory, primarily associated, previous literature |
| الوصف: |
The performance of ECG delineation using the proposed DAE-ConvBiLSTM model. |
| نوع الوثيقة: |
dataset |
| اللغة: |
unknown |
| العلاقة: |
https://figshare.com/articles/dataset/The_performance_of_ECG_delineation_using_the_proposed_DAE-ConvBiLSTM_model_/21798420Test |
| DOI: |
10.1371/journal.pone.0277932.t003 |
| الإتاحة: |
https://doi.org/10.1371/journal.pone.0277932.t003Test |
| حقوق: |
CC BY 4.0 |
| رقم الانضمام: |
edsbas.E7ED99C9 |
| قاعدة البيانات: |
BASE |
