Zobrazeno 1 - 10
of 752
pro vyhledávání: '"Tang Xuemei"'
Autor:
Li Siqi, Tang Xuemei
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
The effective development of Civic Education work in colleges and universities can promote the cultivation of high-quality talents. Starting from Internet information technology, this paper constructs a digital platform for Civic Education work, in w
Externí odkaz:
https://doaj.org/article/2756ba461cde46b0b187f56cfefd54df
Autor:
LIU Haimei, ZHANG Tianyu, MA Le, ZHANG Zhiyong, XU Meng, ZHANG Tao, XU Hong, TANG Xuemei, YANG Sirui, YU Haiguo, SONG Hongmei, SUN Li
Publikováno v:
Xiehe Yixue Zazhi, Vol 14, Iss 2, Pp 278-284 (2023)
Objective To investigate the clinical features and treatment outcomes of chronic non-bacterial osteomyelitis (CNO) from five tertiary pediatric rheumatology services in China and provide possible treatment options for clinicians. Methods In this mult
Externí odkaz:
https://doaj.org/article/05de0893b2274d9bb596ac6b0ad713dd
Autor:
QIU Luyao, TANG Wenjing, YANG Lu, LYU Ge, CHEN Junjie, SUN Gan, WANG Yanping, ZHOU Lina, AN Yunfei, ZHANG Zhiyong, TANG Xuemei, ZHAO Xiaodong, DU Hongqiang
Publikováno v:
Xiehe Yixue Zazhi, Vol 14, Iss 2, Pp 373-378 (2023)
Objective To analyze the clinical phenotype and immunological characteristics of a patient with heterozygous mutation of PTEN and enrich the clinical phenotypes related to PTEN mutation. Methods A retrospective analysis of the clinical data of a pati
Externí odkaz:
https://doaj.org/article/b9f6c9b241a34069a7a2ce97779fef2d
Autor:
ZHANG Junmei, ZHAO Xiaozhen, TANG Xuemei, ZHAO Yi'nan, LI Li, GAO Fengqiao, SHI Xinwei, JIN Yanliang, ZHANG Yu, CAO Lanfang, YIN Wei, XIAO Jihong, KUANG Weiying, DENG Jianghong, WANG Jiang, TAN Xiaohua, LI Chao, LI Shipeng, XUE Haiyan, LIU Cuihua, LIU Xiaohui, ZHAO Dongmei, CHEN Yuqing, ZHENG Wenjie, LI Caifeng
Publikováno v:
罕见病研究, Vol 1, Iss 3, Pp 252-258 (2022)
Objective To study the demographic and clinical characteristics, correlation of genotype and phenotype and treatment of Blau syndrome to facilitate early diagnosis and timely treatment of Blau syndrome. Methods Seventy-two patients with Blau syndrome
Externí odkaz:
https://doaj.org/article/44e1f73a2a7240a693342445afb98414
The literature review is a crucial form of academic writing that involves complex processes of literature collection, organization, and summarization. The emergence of large language models (LLMs) has introduced promising tools to automate these proc
Externí odkaz:
http://arxiv.org/abs/2412.13612
Autor:
Jiang, Yuncheng, Feng, Chun-Mei, Ren, Jinke, Wei, Jun, Zhang, Zixun, Hu, Yiwen, Liu, Yunbi, Sun, Rui, Tang, Xuemei, Du, Juan, Wan, Xiang, Xu, Yong, Du, Bo, Gao, Xin, Wang, Guangyu, Zhou, Shaohua, Cui, Shuguang, Goh, Rick Siow Mong, Liu, Yong, Li, Zhen
Ultrasound imaging is widely used in clinical diagnosis due to its non-invasive nature and real-time capabilities. However, conventional ultrasound diagnostics face several limitations, including high dependence on physician expertise and suboptimal
Externí odkaz:
http://arxiv.org/abs/2411.16380
As synthetic data becomes increasingly prevalent in training language models, particularly through generated dialogue, concerns have emerged that these models may deviate from authentic human language patterns, potentially losing the richness and cre
Externí odkaz:
http://arxiv.org/abs/2409.15890
Autor:
Jiang, Yuncheng, Hu, Yiwen, Zhang, Zixun, Wei, Jun, Feng, Chun-Mei, Tang, Xuemei, Wan, Xiang, Liu, Yong, Cui, Shuguang, Li, Zhen
Endorectal ultrasound (ERUS) is an important imaging modality that provides high reliability for diagnosing the depth and boundary of invasion in colorectal cancer. However, the lack of a large-scale ERUS dataset with high-quality annotations hinders
Externí odkaz:
http://arxiv.org/abs/2408.10067
Natural Language Processing (NLP) plays a pivotal role in the realm of Digital Humanities (DH) and serves as the cornerstone for advancing the structural analysis of historical and cultural heritage texts. This is particularly true for the domains of
Externí odkaz:
http://arxiv.org/abs/2403.15088
Autor:
Tang, Xuemei, Wang, Jun
Recently, large language models (LLMs) have been successful in relational extraction (RE) tasks, especially in the few-shot learning. An important problem in the field of RE is long-tailed data, while not much attention is paid to this problem using
Externí odkaz:
http://arxiv.org/abs/2402.14373