Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Yeongjoon Gil"'
Autor:
Ju Young Kim, Il‐Young Oh, Hyejin Lee, Ji Hyun Lee, Youngjin Cho, Yeongjoon Gil, Sunghoon Jung, Dae In Kim, Myung Geun Shin, Joo Yeon Yoo, Jeong Yeon Kwak
Publikováno v:
Journal of Arrhythmia, Vol 39, Iss 3, Pp 422-429 (2023)
Abstract Background Detecting high‐risk arrhythmia is important in diagnosing patients with palpitations. We compared the diagnostic accuracies of 7‐day patch‐type electrocardiographic (ECG) monitoring and 24‐h Holter monitoring for detecting
Externí odkaz:
https://doaj.org/article/b1cc1a64b9a84be59da34a2095b703d4
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 19, Iss 1, Pp 1-6 (2019)
Abstract Background The global age-adjusted mortality rate related to atrial fibrillation (AF) registered a rapid growth in the last four decades, i.e., from 0.8 to 1.6 and 0.9 to 1.7 per 100,000 for men and women during 1990–2010, respectively. In
Externí odkaz:
https://doaj.org/article/7b6d48b0606b4f0cba70a9ddb719b2e9
Autor:
Kwang-Sig Lee, Hyun-Joon Park, Ji Eon Kim, Hee Jung Kim, Sangil Chon, Sangkyu Kim, Jaesung Jang, Jin-Kook Kim, Seongbin Jang, Yeongjoon Gil, Ho Sung Son
Publikováno v:
Sensors, Vol 22, Iss 5, p 1776 (2022)
The importance of an embedded wearable device with automatic detection and alarming cannot be overstated, given that 15–30% of patients with atrial fibrillation are reported to be asymptomatic. These asymptomatic patients do not seek medical care,
Externí odkaz:
https://doaj.org/article/20c1be0f5f684b73b3dcc2e43fcd1a84
Publikováno v:
Applied Sciences, Vol 10, Iss 18, p 6495 (2020)
Accurate electrocardiogram (ECG) interpretation is crucial in the clinical ECG workflow because it is most likely associated with a disease that can cause major problems in the body. In this study, we proposed an ECG-signal multi-classification model
Externí odkaz:
https://doaj.org/article/105fd1ad13da4b49991bc3567a4a5ce3
Publikováno v:
Sensors, Vol 12, Iss 10, Pp 13225-13248 (2012)
Currently considerable research is being directed toward developing methodologies for controlling emotion or releasing stress. An applied branch of the basic field of psychophysiology, known as biofeedback, has been developed to fulfill clinical and
Externí odkaz:
https://doaj.org/article/0f3e92d0c8424b629306c8a86ef7d212
Publikováno v:
Sensors, Vol 12, Iss 8, Pp 10381-10394 (2012)
Background: Human life can be further improved if diseases and disorders can be predicted before they become dangerous, by correctly recognizing signals from the human body, so in order to make disease detection more precise, various body-signals nee
Externí odkaz:
https://doaj.org/article/10a3bb586a9b4bf2a0b58606088810e0
Autor:
Ju Young Kim, Il‐Young Oh, Hyejin Lee, Ji Hyun Lee, Youngjin Cho, Yeongjoon Gil, Sunghoon Jung, Dae In Kim, Myung Geun Shin, Joo Yeon Yoo, Jeong Yeon Kwak
Publikováno v:
Journal of Arrhythmia.
Autor:
Sunghoon Jung, Junho An, Jin-Kook Kim, Junsang Park, Il-Young Oh, Yeongjoon Gil, Yoojin Jang, Kwanglo Lee
Publikováno v:
Computer methods and programs in biomedicine. 214
Background and objectives: Most deep-learning-related methodologies for electrocardiogram (ECG) classification are focused on finding an optimal deep-learning architecture to improve classification performance. However, in this study, we proposed a m
Publikováno v:
Applied Sciences, Vol 10, Iss 6495, p 6495 (2020)
Applied Sciences
Volume 10
Issue 18
Applied Sciences
Volume 10
Issue 18
Accurate electrocardiogram (ECG) interpretation is crucial in the clinical ECG workflow because it is most likely associated with a disease that can cause major problems in the body. In this study, we proposed an ECG-signal multi-classification model
Additional file 1: Figure S1. Electrocardiogram Wave. A Normal. B Atrial Fibrillation vs. Normal. The atrial-fibrillation rhythm in the top does not have a P wave (purple arrow) of the normal rhythm in the bottom. Figure S2. Preprocessing. A. Removin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9bf74f1af30313293e56f5f4a5b97d9