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5,738 results on '"Yuan, Ting"'

113. Factors Impacting Fall Severity in Hospitalized Patients: A Retrospective Cohort Study

Author

Sen-Yung Liu, Yu-Kai Yang, Chew-Teng Kor, Yi-Wei Sun, Hsin-Yu Wang, Yuan-Ting Yang, and Ming-Chih Chou

Subjects
fall-risk-increasing drugs (FRIDs), severity of fall, hospitalized patients, Medicine
Abstract

Objectives: This retrospective case-controlled study aimed to evaluate the association between the severity of fall-related injuries and fall-risk-increasing drugs (FRIDs) in hospitalized patients. Methods: Data were collected from Changhua Christian Hospital, Taiwan, of all adult inpatients who experienced falls between January 2017 and December 2021, and were divided into two groups based on whether they sustained severe fall-related injuries. Retrospective data that may affect the severity of fall-related injuries and the use of FRIDs were investigated. Results: Among 1231 documented cases of falls, 26 patients sustained severe fall-related injuries. Older patients and those with osteoporosis were more susceptible to more severe injuries from a fall. The use of mobility aids and osteoporosis medications showed protective effects against fall injuries. No significant association was observed between fall-related injuries and comorbidities or FRIDs. Multivariate analysis confirmed the inverse correlation between the use of mobility aids, osteoporosis medications, and fall severity. Patients with osteoporosis exhibited significantly higher odds of sustaining more severe injuries with a fall (odds ratio = 3.02, 95% confidence interval: 1.21–7.53). Conclusions: This study highlights the importance of addressing risk factors associated with fall severity among hospitalized patients. Providing mobility aids to persons at greater risk.

Published
2024
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119. Emerging sensing and modeling technologies for wearable and cuffless blood pressure monitoring

Author

Lei Zhao, Cunman Liang, Yan Huang, Guodong Zhou, Yiqun Xiao, Nan Ji, Yuan-Ting Zhang, and Ni Zhao

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Abstract Cardiovascular diseases (CVDs) are a leading cause of death worldwide. For early diagnosis, intervention and management of CVDs, it is highly desirable to frequently monitor blood pressure (BP), a vital sign closely related to CVDs, during people’s daily life, including sleep time. Towards this end, wearable and cuffless BP extraction methods have been extensively researched in recent years as part of the mobile healthcare initiative. This review focuses on the enabling technologies for wearable and cuffless BP monitoring platforms, covering both the emerging flexible sensor designs and BP extraction algorithms. Based on the signal type, the sensing devices are classified into electrical, optical, and mechanical sensors, and the state-of-the-art material choices, fabrication methods, and performances of each type of sensor are briefly reviewed. In the model part of the review, contemporary algorithmic BP estimation methods for beat-to-beat BP measurements and continuous BP waveform extraction are introduced. Mainstream approaches, such as pulse transit time-based analytical models and machine learning methods, are compared in terms of their input modalities, features, implementation algorithms, and performances. The review sheds light on the interdisciplinary research opportunities to combine the latest innovations in the sensor and signal processing research fields to achieve a new generation of cuffless BP measurement devices with improved wearability, reliability, and accuracy.

Published
2023
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121. Chirality Nets for Human Pose Regression

Author

Yeh, Raymond A., Hu, Yuan-Ting, and Schwing, Alexander G.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

We propose Chirality Nets, a family of deep nets that is equivariant to the "chirality transform," i.e., the transformation to create a chiral pair. Through parameter sharing, odd and even symmetry, we propose and prove variants of standard building blocks of deep nets that satisfy the equivariance property, including fully connected layers, convolutional layers, batch-normalization, and LSTM/GRU cells. The proposed layers lead to a more data efficient representation and a reduction in computation by exploiting symmetry. We evaluate chirality nets on the task of human pose regression, which naturally exploits the left/right mirroring of the human body. We study three pose regression tasks: 3D pose estimation from video, 2D pose forecasting, and skeleton based activity recognition. Our approach achieves/matches state-of-the-art results, with more significant gains on small datasets and limited-data settings., Comment: Accepted to NeurIPS2019

Published
2019

134. Increased di-(2-ethylhexyl) phthalate exposure poses a differential risk for adult asthma clusters

Author

Hsu, Yuan-Ting, Wu, Chao-Chien, Wang, Chin-Chou, Sheu, Chau-Chyun, Yang, Yi-Hsin, Cheng, Ming-Yen, Lai, Ruay-Sheng, Leung, Sum-Yee, Lin, Chi-Cheng, Wei, Yu-Feng, Lai, Yung-Fa, Cheng, Meng-Hsuan, Chen, Huang-Chi, Yang, Chih-Jen, Wang, Chien-Jen, Liu, Huei-Ju, Chen, Hua-Ling, Hung, Chih-Hsing, Lee, Chon-Lin, Huang, Ming-Shyan, and Huang, Shau-Ku

Published
2024
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147. NVIDIA FLARE: Federated Learning from Simulation to Real-World.

Author

Holger R. Roth, Yan Cheng, Yuhong Wen, Isaac Yang, Ziyue Xu 0001, Yuan-Ting Hsieh, Kristopher Kersten, Ahmed Harouni, Can Zhao 0001, Kevin Lu, Zhihong Zhang 0001, Wenqi Li 0001, Andriy Myronenko, Dong Yang 0005, Sean Yang, Nicola Rieke, Abood Quraini, Chester Chen, Daguang Xu, Nic Ma, Prerna Dogra, Mona Flores, and Andrew Feng

Published
2023

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