Zobrazeno 1 - 10
of 2 811
pro vyhledávání: '"Ding Cheng"'
Autor:
Han, Yu, Ding, Cheng
The electrocardiogram (ECG) is ubiquitous across various healthcare domains, such as cardiac arrhythmia detection and sleep monitoring, making ECG analysis critically essential. Traditional deep learning models for ECG are task-specific, with a narro
Externí odkaz:
http://arxiv.org/abs/2410.19877
Autor:
Liu, Cheng, Yan, Xuyang, Zhang, Zekun, Ding, Cheng, Zhao, Tianhao, Jannati, Shaya, Martinez, Cynthia, Stout, Dietrich
Action recognition has witnessed the development of a growing number of novel algorithms and datasets in the past decade. However, the majority of public benchmarks were constructed around activities of daily living and annotated at a rather coarse-g
Externí odkaz:
http://arxiv.org/abs/2410.08410
The electrocardiogram (ECG) remains a fundamental tool in cardiac diagnostics, yet its interpretation traditionally reliant on the expertise of cardiologists. The emergence of deep learning has heralded a revolutionary era in medical data analysis, p
Externí odkaz:
http://arxiv.org/abs/2409.07975
Publikováno v:
Quantum Information Processing,23:319,(2024)
It is well-known that maximally entangled GHZ states can achieve perfect teleportation and superdense coding, whereas maximally entangled W states cannot. However, it has been demonstrated that there exists a special class of non-maximally entangled
Externí odkaz:
http://arxiv.org/abs/2407.07626
Foundation models, especially those using transformers as backbones, have gained significant popularity, particularly in language and language-vision tasks. However, large foundation models are typically trained on high-quality data, which poses a si
Externí odkaz:
http://arxiv.org/abs/2404.17667
Autor:
Yan, Runze, Ding, Cheng, Xiao, Ran, Fedorov, Aleksandr, Lee, Randall J, Nahab, Fadi, Hu, Xiao
Atrial fibrillation (AF), a common cardiac arrhythmia, significantly increases the risk of stroke, heart disease, and mortality. Photoplethysmography (PPG) offers a promising solution for continuous AF monitoring, due to its cost efficiency and integ
Externí odkaz:
http://arxiv.org/abs/2404.15353
Autor:
Liu, Darren, Ding, Cheng, Bold, Delgersuren, Bouvier, Monique, Lu, Jiaying, Shickel, Benjamin, Jabaley, Craig S., Zhang, Wenhui, Park, Soojin, Young, Michael J., Wainwright, Mark S., Clermont, Gilles, Rashidi, Parisa, Rosenthal, Eric S., Dimisko, Laurie, Xiao, Ran, Yoon, Joo Heung, Yang, Carl, Hu, Xiao
The field of healthcare has increasingly turned its focus towards Large Language Models (LLMs) due to their remarkable performance. However, their performance in actual clinical applications has been underexplored. Traditional evaluations based on qu
Externí odkaz:
http://arxiv.org/abs/2401.13588
This paper explores the challenges in evaluating machine learning (ML) models for continuous health monitoring using wearable devices beyond conventional metrics. We state the complexities posed by real-world variability, disease dynamics, user-speci
Externí odkaz:
http://arxiv.org/abs/2312.02300
Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with significant health ramifications, including an elevated susceptibility to ischemic stroke, heart disease, and heightened mortality. Photoplethysmography (PPG) has emerged as a
Externí odkaz:
http://arxiv.org/abs/2310.14155
Autor:
Guo, Zhicheng, Ding, Cheng, Do, Duc H., Shah, Amit, Lee, Randall J., Hu, Xiao, Rudin, Cynthia
Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. It is associated with an increased risk of stroke, heart failure, and other cardiovascular complications, but can be clinically silent. Passive AF monitoring with wearables may h
Externí odkaz:
http://arxiv.org/abs/2310.09203