Zobrazeno 1 - 10
of 941
pro vyhledávání: '"XiaoQin Zhang"'
Publikováno v:
Journal of Health, Population and Nutrition, Vol 43, Iss 1, Pp 1-8 (2024)
Abstract Purpose To evaluate the therapeutic efficacy of intravenous amoxicillin clavulanate potassium combined with nebulized budesonide and ambroxol hydrochloride in pediatric community-acquired pneumonia (CAP) and its impact across various microbi
Externí odkaz:
https://doaj.org/article/4ef742b1b9354fe0a38053921afdb250
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract The OVATE gene family plays an important role in regulating the development of plant organs and resisting stress, but its expression characteristics and functions in sorghum have not been revealed. In this study, we identified 26 OVATE genes
Externí odkaz:
https://doaj.org/article/1b00aa7c3b7f4023a285540c8fb9787a
Publikováno v:
Frontiers in Pharmacology, Vol 15 (2024)
BackgroundMelastoma dodecandrum Lour. (MD), a traditional botanical drug known for its hypoglycemic, antioxidant, and anti-inflammatory properties, is commonly used to treat diabetes, osteoarthritis, and osteoporosis. However, its specific active com
Externí odkaz:
https://doaj.org/article/aedf1e8b322d4b96933684030d7dd108
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 36, Iss 8, Pp 102168- (2024)
Current knowledge graph-based recommendation methods heavily rely on high-quality knowledge graphs, often falling short in effectively addressing issues such as the cold start problem and heterogeneous noise in user interactions. This leads to biases
Externí odkaz:
https://doaj.org/article/4b6415b538ea4afc9e70ddf92ced80e7
Autor:
Yinchen SU, Xiaoqin ZHANG
Publikováno v:
CT Lilun yu yingyong yanjiu, Vol 33, Iss 3, Pp 325-331 (2024)
Objective: To investigate the applicability of artificial intelligence-assisted diagnosis system in detecting pulmonary nodules and distinguishing benign and malignant nodules. Methods: Patients who underwent chest computed tomography (CT) from March
Externí odkaz:
https://doaj.org/article/e8dd8feaf456484aa1580874d2a8ea7b
Autor:
Runyuan Wang, Xingcai Chen, Xiaoqin Zhang, Ping He, Jinfeng Ma, Huilin Cui, Ximei Cao, Yongjian Nian, Ximing Xu, Wei Wu, Yi Wu
Publikováno v:
Cancer Medicine, Vol 13, Iss 18, Pp n/a-n/a (2024)
Abstract Objective To create a deep‐learning automatic segmentation model for esophageal cancer (EC), metastatic lymph nodes (MLNs) and their adjacent structures using the UperNet Swin network and computed tomography angiography (CTA) images and to
Externí odkaz:
https://doaj.org/article/128807c0ec4d4b88bc39b356ced28a3b
Publikováno v:
Frontiers in Immunology, Vol 15 (2024)
As an effective treatment for diabetes, islet transplantation has garnered significant attention and research in recent years. However, immune rejection and the toxicity of immunosuppressive drugs remain critical factors influencing the success of is
Externí odkaz:
https://doaj.org/article/5cbe76ed0e0243c9ac62999d15825d34
Publikováno v:
CT Lilun yu yingyong yanjiu, Vol 33, Iss 2, Pp 197-205 (2024)
Background: To investigate the diagnostic value of computed tomography (CT)-guided aspiration biopsy combined with rapid field evaluation for pulmonary lesions. Methods: The PubMed and EMBASE databases were searched systematically for studies related
Externí odkaz:
https://doaj.org/article/cad375455cdf42f384795feca785f1ae
Autor:
Xiaoqin Zhang, Pei-Hua Lang
Publikováno v:
IEEE Access, Vol 12, Pp 113910-113917 (2024)
The differential tracking for a given signal is a well-known and challenging problem in control theory and practice. In this note, we introduce a novel method to design the differentiators. The proposed differentiator, in contrast to existing differe
Externí odkaz:
https://doaj.org/article/ff5e606747904dabaefa881c2df3d167
Publikováno v:
IEEE Access, Vol 12, Pp 29571-29582 (2024)
In this paper, a method for orthogonal tensor recovery based on non-convex regularization and rank estimation (OTRN-RE) is proposed, which aims to accurately recover the low-rank and sparse components of the tensor. Specifically, a new low-rank tenso
Externí odkaz:
https://doaj.org/article/b1f639bcdc9341ea87bbc36c3c7cfb2c