Zobrazeno 1 - 10
of 562
pro vyhledávání: '"Ju, Chao"'
In radial quantization, the ground states of a gauge theory on ADE singularities $R^4/\Gamma$ are characterized by flat connections that are maps from $\Gamma$ to the gauge group. We study Class S theory of type $A_1$ on a Riemann surface of genus $g
Externí odkaz:
http://arxiv.org/abs/2404.12446
Autor:
Ju, Chao
Classically, the ground states of $\mathcal{N}=4$ supersymmetric Yang-Mills theory on $\mathbb{R}\times S^3/\Gamma$ where $\Gamma$ is a discrete ADE subgroup of $SU(2)$ are represented by flat Wilson lines winding around the ADE singularity. By a dua
Externí odkaz:
http://arxiv.org/abs/2311.18223
Autor:
Liu, Zhengliang, Li, Yiwei, Shu, Peng, Zhong, Aoxiao, Yang, Longtao, Ju, Chao, Wu, Zihao, Ma, Chong, Luo, Jie, Chen, Cheng, Kim, Sekeun, Hu, Jiang, Dai, Haixing, Zhao, Lin, Zhu, Dajiang, Liu, Jun, Liu, Wei, Shen, Dinggang, Liu, Tianming, Li, Quanzheng, Li, Xiang
This paper introduces Radiology-Llama2, a large language model specialized for radiology through a process known as instruction tuning. Radiology-Llama2 is based on the Llama2 architecture and further trained on a large dataset of radiology reports t
Externí odkaz:
http://arxiv.org/abs/2309.06419
Autor:
Liu, Zhengliang, Zhong, Aoxiao, Li, Yiwei, Yang, Longtao, Ju, Chao, Wu, Zihao, Ma, Chong, Shu, Peng, Chen, Cheng, Kim, Sekeun, Dai, Haixing, Zhao, Lin, Sun, Lichao, Zhu, Dajiang, Liu, Jun, Liu, Wei, Shen, Dinggang, Li, Xiang, Li, Quanzheng, Liu, Tianming
We introduce Radiology-GPT, a large language model for radiology. Using an instruction tuning approach on an extensive dataset of radiology domain knowledge, Radiology-GPT demonstrates superior performance compared to general language models such as
Externí odkaz:
http://arxiv.org/abs/2306.08666
Autor:
Tsair-Fwu Lee, Chien-Liang Chiu, Yen-Hsien Liu, Chu-Ho Chang, Jen-Chung Shao, Shih-Sian Guo, Yi-Lun Liao, Chia-Hui Chen, Chin-Dar Tseng, Pei-Ju Chao, Shen-Hao Lee
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract The study aims to develop an abnormal body temperature probability (ABTP) model for dairy cattle, utilizing environmental and physiological data. This model is designed to enhance the management of heat stress impacts, providing an early war
Externí odkaz:
https://doaj.org/article/69915a2db126418aa2aa8d43b7764a75
Autor:
Tsair-Fwu Lee, Yen-Hsien Liu, Chu-Ho Chang, Chien-Liang Chiu, Chih-Hsueh Lin, Jen-Chung Shao, Yu-Cheng Yen, Guang-Zhi Lin, Jack Yang, Chin-Dar Tseng, Fu-Min Fang, Pei-Ju Chao, Shen-Hao Lee
Publikováno v:
Radiation Oncology, Vol 19, Iss 1, Pp 1-11 (2024)
Abstract Purpose This study aims to develop an ensemble machine learning-based (EML-based) risk prediction model for radiation dermatitis (RD) in patients with head and neck cancer undergoing proton radiotherapy, with the goal of achieving superior p
Externí odkaz:
https://doaj.org/article/df84e7e0d00c41729986d40fc45a232f
Autor:
Ju, Chao
The Hilbert space of level $q$ Chern-Simons theory of gauge group $G$ of the ADE type quantized on $T^2$ can be represented by points that lie on the weight lattice of the Lie algebra $\mathfrak{g}$ up to some discrete identifications. Of special sig
Externí odkaz:
http://arxiv.org/abs/2304.11830
Autor:
Isabel G. Scalia, Juan M. Farina, Rachel Wraith, Lisa Brown, Mohammed Tiseer Abbas, Milagros Pereyra, Mohamed Allam, Ahmed K. Mahmoud, Moaz A. Kamel, Timothy Barry, F. David Fortuin, Steven J. Lester, John Sweeney, Kristen A. Sell-Dottin, Mohamad Alkhouli, David R. Holmes, Chieh-Ju Chao, Said Alsidawi, Chadi Ayoub, Reza Arsanjani
Publikováno v:
Heliyon, Vol 10, Iss 11, Pp e32378- (2024)
Background: Residual mitral regurgitation (MR) is frequent after transcatheter edge-to-edge repair (TEER). There is controversy regarding the clinical impact of residual MR and its quantitative assessment by transthoracic echocardiography (TTE), whic
Externí odkaz:
https://doaj.org/article/abce7436be3942d58f641167786192e6
Autor:
Tsair-Fwu Lee, Yang-Wei Hsieh, Pei-Ying Yang, Chi-Hung Tseng, Shen-Hao Lee, Jack Yang, Liyun Chang, Jia-Ming Wu, Chin-Dar Tseng, Pei-Ju Chao
Publikováno v:
Radiation Oncology, Vol 19, Iss 1, Pp 1-21 (2024)
Abstract Purpose The study aims to enhance the efficiency and accuracy of literature reviews on normal tissue complication probability (NTCP) in head and neck cancer patients using radiation therapy. It employs meta-analysis (MA) and natural language
Externí odkaz:
https://doaj.org/article/89dec3a1cb2d4b93b408dfe57e208d93
Autor:
Chieh-Ju Chao, MD, Timothy Barry, MB, BCh, BAO, Amith Seri, MBBS, Ahmed El Shaer, MBBS, Nadia Chavez Ponce, MD, Soham Chakraborty, BS, Sean Smith, MD, Mohamad Alkhouli, MD, Jeremy Thaden, MD, David Fortuin, MD, John P. Sweeney, MD, Mackram Eleid, MD, Charanjit S. Rihal, MD, David R. Holmes, MD, Peter M. Pollak, MD, Abdallah El Sabbagh, MD, Steven J. Lester, MD, Jae K. Oh, MD, Win-Kuang Shen, MD, Imon Banerjee, PhD, Reza Arsanjani, MD
Publikováno v:
Mayo Clinic Proceedings: Digital Health, Vol 1, Iss 3, Pp 381-392 (2023)
Objective: To identify prognostically distinct phenotype clusters in transcatheter edge-to-edge repair (TEER) patients based on topological data analysis (TDA), which was never used to assess the heterogeneous TEER population. Patients and Methods: P
Externí odkaz:
https://doaj.org/article/abcc2a5894004ce996bd0f11c2f761f1