Výsledky vyhledávání - "YUAN Xiaohan"

Akademický článek

Multi-source Feature Classification Model of Pancreatic Mucinous and Serous Cystic Neoplasms Based on Deep Learning

Autor: XU Zhenshun, YUAN Xiaohan, HUANG Ziheng, SHAO Chengwei, WU Jie, BIAN Yun

Publikováno v: Chinese Journal of Magnetic Resonance, Vol 41, Iss 1, Pp 19-29 (2024)

This study aims to classify and differentiate mucinous and serous cystic neoplasms of the pancreas using a multi-source feature classification model based on deep learning for preoperative auxiliary diagnosis. Deep learning features and radiomics fea

Externí odkaz: https://doaj.org/article/0f39515cb3b044709275e788cc131751

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S-Eval: Automatic and Adaptive Test Generation for Benchmarking Safety Evaluation of Large Language Models

Autor: Yuan, Xiaohan, Li, Jinfeng, Wang, Dongxia, Chen, Yuefeng, Mao, Xiaofeng, Huang, Longtao, Xue, Hui, Wang, Wenhai, Ren, Kui, Wang, Jingyi

Large Language Models have gained considerable attention for their revolutionary capabilities. However, there is also growing concern on their safety implications, making a comprehensive safety evaluation for LLMs urgently needed before model deploym

Externí odkaz: http://arxiv.org/abs/2405.14191

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Prompting Frameworks for Large Language Models: A Survey

Autor: Liu, Xiaoxia, Wang, Jingyi, Sun, Jun, Yuan, Xiaohan, Dong, Guoliang, Di, Peng, Wang, Wenhai, Wang, Dongxia

Since the launch of ChatGPT, a powerful AI Chatbot developed by OpenAI, large language models (LLMs) have made significant advancements in both academia and industry, bringing about a fundamental engineering paradigm shift in many areas. While LLMs a

Externí odkaz: http://arxiv.org/abs/2311.12785

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4D Myocardium Reconstruction with Decoupled Motion and Shape Model

Autor: Yuan, Xiaohan, Liu, Cong, Wang, Yangang

Estimating the shape and motion state of the myocardium is essential in diagnosing cardiovascular diseases.However, cine magnetic resonance (CMR) imaging is dominated by 2D slices, whose large slice spacing challenges inter-slice shape reconstruction

Externí odkaz: http://arxiv.org/abs/2308.14083

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DiffuseExpand: Expanding dataset for 2D medical image segmentation using diffusion models

Autor: Shao, Shitong, Yuan, Xiaohan, Huang, Zhen, Qiu, Ziming, Wang, Shuai, Zhou, Kevin

Dataset expansion can effectively alleviate the problem of data scarcity for medical image segmentation, due to privacy concerns and labeling difficulties. However, existing expansion algorithms still face great challenges due to their inability of g

Externí odkaz: http://arxiv.org/abs/2304.13416

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