Zobrazeno 1 - 10
of 19 040
pro vyhledávání: '"On-Yu Hong"'
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-12 (2022)
Abstract Sirtuin 6 (SIRT6) regulation is involved in carcinogenesis. However, its role in breast cancer (BC) metastasis remains unclear. We investigated the effects of SIRT6 on protein kinase C activator- and cytokine-mediated cancer cell invasion an
Externí odkaz:
https://doaj.org/article/5409bb3a6d324ab88638731dc56f82ed
Autor:
Zhang, Wei-Yang, Dong, Feng-Lian, Wei, Zhi-Wei, Wang, Yan-Ru, Xu, Ze-Jin, Chen, Wei-Kun, Dai, Yu-Hong
The distributed recursion (DR) algorithm is an effective method for solving the pooling problem that arises in many applications. It is based on the well-known P-formulation of the pooling problem, which involves the flow and quality variables; and i
Externí odkaz:
http://arxiv.org/abs/2411.09554
Autor:
Wang, Junda, Li, Weijian, Wang, Han, Lyu, Hanjia, Thirukumaran, Caroline P., Mesfin, Addisu, Yu, Hong, Luo, Jiebo
Causal inference and model interpretability are gaining increasing attention, particularly in the biomedical domain. Despite recent advance, decorrelating features in nonlinear environments with human-interpretable representations remains underexplor
Externí odkaz:
http://arxiv.org/abs/2411.06338
Despite significant advancements, large language models (LLMs) still struggle with providing accurate answers when lacking domain-specific or up-to-date knowledge. Retrieval-Augmented Generation (RAG) addresses this limitation by incorporating extern
Externí odkaz:
http://arxiv.org/abs/2411.01705
Autor:
Wang, Junda, Ting, Yujan, Chen, Eric Z., Tran, Hieu, Yu, Hong, Huang, Weijing, Chen, Terrence
Multimodal large language models (MLLMs) have made significant strides, yet they face challenges in the medical domain due to limited specialized knowledge. While recent medical MLLMs demonstrate strong performance in lab settings, they often struggl
Externí odkaz:
http://arxiv.org/abs/2410.14948
Autor:
Huang, Jiatan, Li, Mingchen, Yao, Zonghai, Yang, Zhichao, Xiao, Yongkang, Ouyang, Feiyun, Li, Xiaohan, Han, Shuo, Yu, Hong
Answering complex real-world questions often requires accurate retrieval from textual knowledge graphs (TKGs). The scarcity of annotated data, along with intricate topological structures, makes this task particularly challenging. As the nature of rel
Externí odkaz:
http://arxiv.org/abs/2410.13987
Autor:
Yao, Zonghai, Parashar, Aditya, Zhou, Huixue, Jang, Won Seok, Ouyang, Feiyun, Yang, Zhichao, Yu, Hong
Automatic question generation (QG) is essential for AI and NLP, particularly in intelligent tutoring, dialogue systems, and fact verification. Generating multiple-choice questions (MCQG) for professional exams, like the United States Medical Licensin
Externí odkaz:
http://arxiv.org/abs/2410.13191
Wikipedia (Wiki) is one of the most widely used and publicly available resources for natural language processing (NLP) applications. Wikipedia Revision History (WikiRevHist) shows the order in which edits were made to any Wiki page since its first mo
Externí odkaz:
http://arxiv.org/abs/2410.04410
Autor:
Yao, Zonghai, Zhang, Zihao, Tang, Chaolong, Bian, Xingyu, Zhao, Youxia, Yang, Zhichao, Wang, Junda, Zhou, Huixue, Jang, Won Seok, Ouyang, Feiyun, Yu, Hong
Artificial intelligence (AI) and large language models (LLMs) in healthcare require advanced clinical skills (CS), yet current benchmarks fail to evaluate these comprehensively. We introduce MedQA-CS, an AI-SCE framework inspired by medical education
Externí odkaz:
http://arxiv.org/abs/2410.01553
Natural Language Processing (NLP) techniques have been increasingly integrated into clinical projects to advance clinical decision-making and improve patient outcomes. Such projects benefit from interdisciplinary team collaborations. This paper explo
Externí odkaz:
http://arxiv.org/abs/2410.00174