Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Xiuyu Huang"'
Publikováno v:
BMC Nursing, Vol 22, Iss 1, Pp 1-15 (2023)
Abstract Background Acceptance-based pain management interventions have been receiving growing attention in cancer pain care. This study aimed to develop a cancer pain management program based on belief modification to improve the cancer pain experie
Externí odkaz:
https://doaj.org/article/e093dbb9b6d045a6a1277b824b78cd30
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 530-543 (2023)
For practical motor imagery (MI) brain-computer interface (BCI) applications, generating a reliable model for a target subject with few MI trials is important since the data collection process is labour-intensive and expensive. In this paper, we addr
Externí odkaz:
https://doaj.org/article/71f105a4fee34aefa927be68d1e9b858
Autor:
Guochuang Chen, Leli Zeng, Bo Bi, Xiuyu Huang, Miaojuan Qiu, Ping Chen, Zhi‐Ying Chen, Yulong He, Yihang Pan, Yu Chen, Jing Zhao
Publikováno v:
Advanced Science, Vol 10, Iss 14, Pp n/a-n/a (2023)
Abstract Ovarian cancer is the most lethal gynecological malignancy. Most patients are diagnosed at an advanced stage with widespread peritoneal dissemination and ascites. Bispecific T‐cell engagers (BiTEs) have demonstrated impressive antitumor ef
Externí odkaz:
https://doaj.org/article/1f86e3085a54490893f6614fecec525e
Autor:
Xiuyu Huang, Miaojuan Qiu, Tianqi Wang, Binbin Li, Shiqiang Zhang, Tianzhi Zhang, Peng Liu, Qiang Wang, Zhi Rong Qian, Chengming Zhu, Meiying Wu, Jing Zhao
Publikováno v:
Journal of Nanobiotechnology, Vol 20, Iss 1, Pp 1-15 (2022)
Abstract Background Ovarian cancer is the most lethal gynecological cancer which is characterized by extensive peritoneal implantation metastasis and malignant ascites. Despite advances in diagnosis and treatment in recent years, the five-year surviv
Externí odkaz:
https://doaj.org/article/91f8b3b5141148af9115dacc2c6de338
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
The classification based on Electroencephalogram (EEG) is a challenging task in the brain-computer interface (BCI) field due to data with a low signal-to-noise ratio. Most current deep learning based studies in this challenge focus on designing a des
Externí odkaz:
https://doaj.org/article/55492afbfd324e759fe5a7ba7023b30f
Engineering Alendronate‐Composed Iron Nanochelator for Efficient Peritoneal Carcinomatosis Treatment
Autor:
Jing Zhao, Xiuyu Huang, Peng Liu, Miaojuan Qiu, Binbin Li, Yingfei Wen, Yongshu Li, Qiang Wang, Meiying Wu, Yu Chen, Yihang Pan
Publikováno v:
Advanced Science, Vol 9, Iss 30, Pp n/a-n/a (2022)
Abstract Iron is an essential element for various cellular metabolism. Cancer cells also have high requirement of iron in their proliferation, invasion, and metastasis processes. Alendronate (ALN), a kind of FDA‐approved bisphosphonates with metal
Externí odkaz:
https://doaj.org/article/c4f54b3f79e14ae9b9b5ddedadeedcd0
Publikováno v:
Land, Vol 12, Iss 5, p 1007 (2023)
The low–carbon transition of farmland use (LCTFU) is an effective measure to coordinate the development of farmland and the environment to meet China’s “dual carbon” and green agricultural transformation goals. We studied the spatial–tempor
Externí odkaz:
https://doaj.org/article/4fb7cc80de9e4317ad577ddd8c58aa5c
Publikováno v:
Stem Cell Research & Therapy, Vol 11, Iss 1, Pp 1-7 (2020)
Abstract Acute respiratory distress syndrome (ARDS) develops rapidly and has a high mortality rate. Survivors usually have low quality of life. Current clinical management strategies are respiratory support and restricted fluid input, and there is no
Externí odkaz:
https://doaj.org/article/cb0011a1664444ab9ea220de6e2f6eba
Publikováno v:
PLoS ONE, Vol 17, Iss 6 (2022)
Recently, a novel electroencephalogram-based brain-computer interface (EVE-BCI) using the vibrotactile stimulus shows great potential for an alternative to other typical motor imagery and visual-based ones. (i) Objective: in this review, crucial aspe
Externí odkaz:
https://doaj.org/article/be238b7ead4c451c9ec5a099b2fb9952
Publikováno v:
Frontiers in Neuroscience, Vol 15 (2021)
Convolutional neural networks (CNNs) have been widely applied to the motor imagery (MI) classification field, significantly improving the state-of-the-art (SoA) performance in terms of classification accuracy. Although innovative model structures are
Externí odkaz:
https://doaj.org/article/853fa185d3e04d2e9e4048a438b9b30c