Zobrazeno 1 - 10
of 1 779
pro vyhledávání: '"TAN Zhen"'
Autor:
Fan Shiqi, Tan Zhen, Peng Zhiyu, Li Shilei, Lei Haoyuan, Qin Yuxiang, Fan Hongyuan, Lin Yuanhua, Zhou Changchun
Publikováno v:
Reviews on Advanced Materials Science, Vol 63, Iss 1, Pp pp. 185-193 (2024)
Due to the uncertainty of trauma or infection, customized bone substitutes are often required in clinic. Meanwhile, excessive use of antibiotics may lead to drug resistance. Therefore, the design of anti-infection bone tissue engineering scaffold is
Externí odkaz:
https://doaj.org/article/a07344d385ad40308733e7a037dadc10
Autor:
TAN Zhen-qiong, JIANG Wen-Jun, YUM Yen-na-cherry, ZHANG Ji, YUM Peter-tak-shing, LI Xiao-hong
Publikováno v:
Jisuanji kexue, Vol 49, Iss 4, Pp 269-281 (2022)
“Learning” is a complex event.Individual's learning effect is affected by many factors.Moreover, different individuals have different learning habits.Therefore, it is challenging for students to plan their learning schedule reasonably according t
Externí odkaz:
https://doaj.org/article/df4617534a2c4f84b5d67afff7251fa0
Autor:
Naeem, Awais, Li, Tianhao, Liao, Huang-Ru, Xu, Jiawei, Mathew, Aby M., Zhu, Zehao, Tan, Zhen, Jaiswal, Ajay Kumar, Salibian, Raffi A., Hu, Ziniu, Chen, Tianlong, Ding, Ying
Accurate diagnosis and prognosis assisted by pathology images are essential for cancer treatment selection and planning. Despite the recent trend of adopting deep-learning approaches for analyzing complex pathology images, they fall short as they oft
Externí odkaz:
http://arxiv.org/abs/2411.17073
Autor:
Li, Dawei, Jiang, Bohan, Huang, Liangjie, Beigi, Alimohammad, Zhao, Chengshuai, Tan, Zhen, Bhattacharjee, Amrita, Jiang, Yuxuan, Chen, Canyu, Wu, Tianhao, Shu, Kai, Cheng, Lu, Liu, Huan
Assessment and evaluation have long been critical challenges in artificial intelligence (AI) and natural language processing (NLP). However, traditional methods, whether matching-based or embedding-based, often fall short of judging subtle attributes
Externí odkaz:
http://arxiv.org/abs/2411.16594
Autor:
Li, Dawei, Tan, Zhen, Qian, Peijia, Li, Yifan, Chaudhary, Kumar Satvik, Hu, Lijie, Shen, Jiayi
While multi-agent systems have been shown to significantly enhance the performance of Large Language Models (LLMs) across various tasks and applications, the dense interaction between scaling agents potentially hampers their efficiency and diversity.
Externí odkaz:
http://arxiv.org/abs/2411.03284
Autor:
Zhang, Ruichen, Yao, Yuguang, Tan, Zhen, Li, Zhiming, Wang, Pan, Liu, Huan, Hu, Jingtong, Liu, Sijia, Chen, Tianlong
Image generation is a prevailing technique for clinical data augmentation for advancing diagnostic accuracy and reducing healthcare disparities. Diffusion Model (DM) has become a leading method in generating synthetic medical images, but it suffers f
Externí odkaz:
http://arxiv.org/abs/2410.22551
Autor:
Beigi, Alimohammad, Jiang, Bohan, Li, Dawei, Kumarage, Tharindu, Tan, Zhen, Shaeri, Pouya, Liu, Huan
Human fact-checkers have specialized domain knowledge that allows them to formulate precise questions to verify information accuracy. However, this expert-driven approach is labor-intensive and is not scalable, especially when dealing with complex mu
Externí odkaz:
http://arxiv.org/abs/2410.04616
Autor:
Hu, Lijie, Liu, Liang, Yang, Shu, Chen, Xin, Tan, Zhen, Ali, Muhammad Asif, Li, Mengdi, Wang, Di
Large Language Models have demonstrated remarkable abilities across various tasks, with Chain-of-Thought (CoT) prompting emerging as a key technique to enhance reasoning capabilities. However, existing research primarily focuses on improving performa
Externí odkaz:
http://arxiv.org/abs/2410.03595
Autor:
Lee, Joseph, Yang, Shu, Baik, Jae Young, Liu, Xiaoxi, Tan, Zhen, Li, Dawei, Wen, Zixuan, Hou, Bojian, Duong-Tran, Duy, Chen, Tianlong, Shen, Li
Predicting phenotypes with complex genetic bases based on a small, interpretable set of variant features remains a challenging task. Conventionally, data-driven approaches are utilized for this task, yet the high dimensional nature of genotype data m
Externí odkaz:
http://arxiv.org/abs/2410.01795
Publikováno v:
Shipin yu jixie, Vol 38, Iss 7, Pp 68-74,79 (2022)
Objective: This study aimed to effectively improve the risk warning and quality and safety supervision of polycyclic aromatic hydrocarbons (PAHs) in spicy strip. Methods: The target compounds in the samples were extracted with acetonitrile and purifi
Externí odkaz:
https://doaj.org/article/38c53f59882f4373a0eb5d1b282fed22