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Development of a deep learning algorithm for atrial fibrillation identification using single lead electrocardiogram

Published 2023 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Author Sun Jung Lee, Yun Kwan Kim, Lanmi Hwang, Kyung Chul Kim, Hee Seok Song Abstract Since it is difficult to detect atrial fibrillation (AF) at an early stage, a method to identify the potential

Fast and Accurate Atrial Fibrillation Detection Using Semantic Segmentation

Published 2022 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Author Kun Wook Jo, Hoo Hyun Kim, Jong Doo Choi, Hee Seok Song Abstract We developed a deep learning model to detects atrial fibrillation by segments the morphological features of fibrillations (F wave).

Evaluation of exercise stage and amount of exercise using wearable electrocardiogram

Published 2022 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Author Jongdoo Choi, Lanmi Hwang, Kunwook Jo, WooSik Yu, Heeseok Song Abstract We developed an algorithm that identifies the exercise levels and amount of exercise with high accuracy using the wearable electrocardiogram MC100 that can

Real-time Parallel Algorithmic System for Processing Multiple Data Simultaneously

Published International Conference on Biomedical Engineering and Applications Author Sung-Jin Ahn, Jong-Doo Choi, Hoo-Hyun Kim, Kyung-Chul Kim, Hee-Seok Song Abstract In this study, we propose a system that analyzes multiple ECG data in real time within a single system. This system is designed with a parallel processing architecture, where algorithm

Efficacy if wearable single-Lead ECG Monitoring during Excercise Stress Testing: A comparative study

Efficacy of Wearable Single-Lead ECG Monitoring during Exercise Stress Testing: A Comparative StudyBackground and Objectives: Few comparative studies have evaluated wearable single-lead electrocardiogram (ECG) devices and standard multi-lead ECG devices during exercise testing. This study aimed to validate the accuracy of a wearable single-lead ECG monitor for recording heart rate

Evaluation of Silicone-Based Gel for the Treatment of Hypertrophic Scarring in Rat Models

Evaluation of Silicone-Based Gel for the Treatment of Hypertrophic Scarring in Rat ModelsSo-Jeong Yim Published JMMR 2024.06 Author So-Jeong Yim, Da-Ye Nam, Da-Hye Choi, Jin Woo, Youngtae Kim, JungHoon Chae, Young-Shin Lee, Ji-Youl Jung

Early prediction of cardiac arrest in the intensive care unit using explainable machine learning

Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective StudyBackground: Cardiac arrest (CA) is one of the leading causes of death among patients in the intensive care unit (ICU). Although many CA prediction models with high sensitivity have been developed to anticipate CA, their