no code implementations • 24 Aug 2023 • Byeong Tak Lee, Yong-Yeon Jo, Joon-Myoung Kwon
Although ECG signals are time-series data, CNN-based models have been shown to outperform other neural networks with different architectures in ECG analysis.
1 code implementation • NeurIPS 2023 • JungWoo Oh, Gyubok Lee, Seongsu Bae, Joon-Myoung Kwon, Edward Choi
As a result, our dataset includes diverse ECG interpretation questions, including those that require a comparative analysis of two different ECGs.
1 code implementation • 9 Mar 2023 • Hyunseung Chung, Jiho Kim, Joon-Myoung Kwon, Ki-Hyun Jeon, Min Sung Lee, Edward Choi
We compare the performance of our model with other representative models in text-to-speech and text-to-image.
no code implementations • 8 Aug 2022 • Radhika Dua, Jiyoung Lee, Joon-Myoung Kwon, Edward Choi
Automatic deep learning-based examination of ECG signals can lead to inaccurate diagnosis, and manual analysis involves rejection of noisy ECG samples by clinicians, which might cost extra time.
1 code implementation • 14 Mar 2022 • JungWoo Oh, Hyunseung Chung, Joon-Myoung Kwon, Dong-gyun Hong, Edward Choi
In this work, we propose an ECG pre-training method that learns both local and global contextual representations for better generalizability and performance on downstream tasks.
no code implementations • 28 Feb 2021 • Yong-Yeon Jo, Young Sang Choi, Jong-Hwan Jang, Joon-Myoung Kwon
The electrocardiogram (ECG) records electrical signals in a non-invasive way to observe the condition of the heart, typically looking at the heart from 12 different directions.