Zobrazeno 1 - 10
of 282
pro vyhledávání: '"Fan Ge"'
Autor:
Fan Ge, Tong Wan, Linling Kong, Bowen Xu, Mengxue Sun, Biao Wang, Shubo Liang, Hao Wang, Xia Zhao
Publikováno v:
Heliyon, Vol 10, Iss 13, Pp e33693- (2024)
The prevention of chronic wound formation has already been a primary subject in wound management, particularly for deep wounds. The electrospun nanofiber membranes hold tremendous potential in the prevention of chronic wounds due to their micro/nano
Externí odkaz:
https://doaj.org/article/5c490f5b20fa4ae28a8b9c5422413c31
Autor:
Ran Zhong, Rui Gao, Wenhai Fu, Caichen Li, Zhenyu Huo, Yuewen Gao, Yi Lu, Feng Li, Fan Ge, Hengjia Tu, Zhixuan You, Jianxing He, Wenhua Liang
Publikováno v:
BMC Medicine, Vol 21, Iss 1, Pp 1-12 (2023)
Abstract Background The sensitivity and specificity of minimal residual disease detected by circulating tumor DNA profiling (ctDNA MRD) in lung cancer, with particular attention to the distinction between landmark strategy and surveillance strategy,
Externí odkaz:
https://doaj.org/article/f6423742605143019a8c34a55af4f349
Publikováno v:
Arthritis Research & Therapy, Vol 25, Iss 1, Pp 1-9 (2023)
Abstract Background Patients with rheumatoid arthritis (RA) have a rising possibility of acquiring certain kinds of cancers than the general public. The causal risk association between RA and hepatocellular carcinoma (HCC) remains unknown. Methods Ge
Externí odkaz:
https://doaj.org/article/d887c5de86b34b81bbfd03654d4510d5
Autor:
Yuzhuo Zhang, Jiangpeng Lin, Zhixuan You, Hengjia Tu, Peng He, Jiarong Li, Rui Gao, Ziyu Liu, Zhiyuan Xi, Zekun Li, Yi Lu, Qiyuan Hu, Chenhui Li, Fan Ge, Zhenyu Huo, Guibin Qiao
Publikováno v:
Frontiers in Immunology, Vol 13 (2022)
BackgroundExploring the cancer risks of rheumatoid arthritis (RA) patients with disease-modifying anti-rheumatic drugs (DMARDs) can help detect, evaluate, and treat malignancies at an early stage for these patients. Thus, a comprehensive analysis was
Externí odkaz:
https://doaj.org/article/a54d0a78fdd54f6381344a35a1496639
Publikováno v:
Frontiers in Microbiology, Vol 13 (2022)
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by persistent abnormally elevated blood sugar levels. T2DM affects millions of people and exerts a significant global public health burden. Danggui Buxue decoction (DBD), a
Externí odkaz:
https://doaj.org/article/3180fa7512ce4e61afdd6aca82866203
Autor:
Xusen Zou, Runchen Wang, Zhao Yang, Qixia Wang, Wenhai Fu, Zhenyu Huo, Fan Ge, Ran Zhong, Yu Jiang, Jiangfu Li, Shan Xiong, Wen Hong, Wenhua Liang
Publikováno v:
Frontiers in Public Health, Vol 10 (2022)
BackgroundFamily socioeconomic position (SEP) in childhood is an important factor to predict some chronic diseases. However, the association between family SEP in childhood and the risk of lung cancer is not clear.MethodsA systematic search was perfo
Externí odkaz:
https://doaj.org/article/6454be1758444b97a09132ad26cbb139
Autor:
Fan Ge, Zhenyu Huo, Yeling Liu, Xiaoqin Du, Rui Wang, Weiyi Lin, Runchen Wang, Jiana Chen, Yi Lu, Yaokai Wen, Huiying Cao, Siyue Shang, Md Eftekhar, Di Gu
Publikováno v:
Comprehensive Psychiatry, Vol 115, Iss , Pp 152308- (2022)
Background: Observational studies analyzing the risk of prostate cancer in schizophrenia patients have generated mixed results. We performed a meta-analysis and a Mendelian randomization (MR) analysis to evaluate the relationship and causality betwee
Externí odkaz:
https://doaj.org/article/ce2e09d1ed29444f83cc1057524d8028
Autor:
Chen, Yuyan, Fu, Qiang, Fan, Ge, Du, Lun, Lou, Jian-Guang, Han, Shi, Zhang, Dongmei, Li, Zhixu, Xiao, Yanghua
Recent years, Pre-trained Language models (PLMs) have swept into various fields of artificial intelligence and achieved great success. However, most PLMs, such as T5 and GPT3, have a huge amount of parameters, fine-tuning them is often expensive and
Externí odkaz:
http://arxiv.org/abs/2407.11033
Autor:
Chen, Yuyan, Wen, Zhihao, Fan, Ge, Chen, Zhengyu, Wu, Wei, Liu, Dayiheng, Li, Zhixu, Liu, Bang, Xiao, Yanghua
Prompt engineering, as an efficient and effective way to leverage Large Language Models (LLM), has drawn a lot of attention from the research community. The existing research primarily emphasizes the importance of adapting prompts to specific tasks,
Externí odkaz:
http://arxiv.org/abs/2407.04118
Autor:
Chen, Yuyan, Fu, Qiang, Yuan, Yichen, Wen, Zhihao, Fan, Ge, Liu, Dayiheng, Zhang, Dongmei, Li, Zhixu, Xiao, Yanghua
Large Language Models (LLMs) have gained widespread adoption in various natural language processing tasks, including question answering and dialogue systems. However, a major drawback of LLMs is the issue of hallucination, where they generate unfaith
Externí odkaz:
http://arxiv.org/abs/2407.04121