Zobrazeno 1 - 10
of 3 350
pro vyhledávání: '"P. Shama"'
Publikováno v:
Rwanda Medical Journal, Vol 78, Iss 4, Pp 32-37 (2021)
INTRODUCTION: Burns are the fourth most common type of injury presenting to the emergency department in Rwanda. However, there is little data on the epidemiology of burn patients, which is needed to inform public health measures for burn prevention.
Externí odkaz:
https://doaj.org/article/5e817b6782924de28a63a2bb559626f0
Deep learning methods are at the forefront of automated epileptic seizure detection and onset zone localization using scalp-EEG. However, the performance of deep learning methods rely heavily on the quality of annotated training datasets. Scalp EEG i
Externí odkaz:
http://arxiv.org/abs/2410.19815
The lack of an automated online platform for reporting citizens' complaints, coupled with the city corporations' struggles in managing them, presents significant challenges. Furthermore, the availability of resources is very limited to higher authori
Externí odkaz:
http://arxiv.org/abs/2410.12882
Interpersonal communication plays a key role in managing people's emotions, especially on digital platforms. Studies have shown that people use social media and consume online content to regulate their emotions and find support for rest and recovery.
Externí odkaz:
http://arxiv.org/abs/2408.07704
Publikováno v:
Rwanda Medical Journal, Vol 78, Iss 4 (2022)
Introduction: Burns are the fourth most common type of injury presenting to the emergency department in Rwanda. However, there is little data on the epidemiology of burn patients, which is needed to inform public health measures for burn prevention.
Externí odkaz:
https://doaj.org/article/b993a97bd1c14f109d399f3c6e297e98
Autor:
Sharma, Dushyant, Fosburgh, James, Dumpala, Sri Harsha, Sastri, Chandramouli Shama, Kruchinin, Stanislav Yu., Naylor, Patrick A.
We explore the recently proposed explainable acoustic neural embedding~(XANE) system that models the background acoustics of a speech signal in a non-intrusive manner. The XANE embeddings are used to estimate specific parameters related to the backgr
Externí odkaz:
http://arxiv.org/abs/2407.06342
Autor:
Dumpala, Sri Harsha, Sharma, Dushyant, Sastri, Chandramouli Shama, Kruchinin, Stanislav, Fosburgh, James, Naylor, Patrick A.
We present a novel method for extracting neural embeddings that model the background acoustics of a speech signal. The extracted embeddings are used to estimate specific parameters related to the background acoustic properties of the signal in a non-
Externí odkaz:
http://arxiv.org/abs/2406.05199
Previous works on depression detection use datasets collected in similar environments to train and test the models. In practice, however, the train and test distributions cannot be guaranteed to be identical. Distribution shifts can be introduced due
Externí odkaz:
http://arxiv.org/abs/2404.05071
Publikováno v:
IET Communications, Vol 18, Iss 20, Pp 1753-1764 (2024)
Abstract Vehicular sensor networks (VSNs) are expected to revolutionize the transportation systems through automated decision‐making. These networks function on the communication between vehicles, traffic infrastructure, and people. One of the majo
Externí odkaz:
https://doaj.org/article/526ded370b8b4c718fc896ddc55bcd8b
Autor:
Azhi ShaMa, MM, Chunlan Ma, BS, Yingying Huang, BS, Jingyue Hu, BS, Chunmei Xu, BS, Zhuxin Li, BS, Jing Wang, MD, PhD, Chunyu Zeng, MD, PhD
Publikováno v:
Texas Heart Institute Journal, Vol 51, Iss 2, Pp 1-8 (2024)
Background: Elevated lipoprotein(a) (Lp[a]) is a risk factor for first atherosclerotic thrombosis events, but the role of elevated Lp(a) in secondary prevention is controversial. This study aimed to retrospectively investigate the influence of elevat
Externí odkaz:
https://doaj.org/article/d086aa81f9f14cf1841c593ad0c5e38b