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Your search keyword '"Zhang, Jin-yuan"' showing total 112 results
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112 results on '"Zhang, Jin-yuan"'

1. Use of Machine Learning for Dosage Individualization of Vancomycin in Neonates

Author

Tang, Bo-Hao, Zhang, Jin-Yuan, Allegaert, Karel, Hao, Guo-Xiang, Yao, Bu-Fan, Leroux, Stephanie, Thomson, Alison H., Yu, Ze, Gao, Fei, Zheng, Yi, Zhou, Yue, Capparelli, Edmund V., Biran, Valerie, Simon, Nicolas, Meibohm, Bernd, Lo, Yoke-Lin, Marques, Remedios, Peris, Jose-Esteban, Lutsar, Irja, Saito, Jumpei, Jacqz-Aigrain, Evelyne, van den Anker, John, Wu, Yue-E., and Zhao, Wei

Published
2023
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6. The crystal structure of poly[aqua-(μ2-4,4′- bis(imidazolyl)biphenyl-κ2N:N′)-(μ2-3-nitrobenzene-1,2-dicarboxylato-κ2O:O′)]copper (II) hydrate, C26H21N5O8Cu

Author

Li Gui-Lian, Liu Meng-Ni, Du Gao-Jing, and Zhang Jin-Yuan

Subjects
2172883, Physics, QC1-999, Crystallography, QD901-999
Abstract

C26H21N5O8Cu, monoclinic, P21/c (no. 14), a = 17.2262(10) Å, b = 7.3474(3) Å, c = 21.1086(11) Å, β = 111.498(6)°, V = 2485.8(2) Å3, Z = 4, Rgt(F) = 0.0629, wRref(F2) = 0.1433, T = 293(2) K.

Published
2022
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7. Machine Learning to Dynamically Predict In-Hospital Venous Thromboembolism After Inguinal Hernia Surgery: Results From the CHAT-1 Study

Author

Yan, Yi–Dan, primary, Yu, Ze, additional, Ding, Lan-Ping, additional, Zhou, Min, additional, Zhang, Chi, additional, Pan, Mang-Mang, additional, Zhang, Jin-Yuan, additional, Wang, Ze-Yuan, additional, Gao, Fei, additional, Li, Hang-Yu, additional, Zhang, Guang-Yong, additional, Lin, Hou-Wen, additional, Wang, Ming-Gang, additional, and Gu, Zhi–Chun, additional

Published
2023
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8. sj-docx-1-cat-10.1177_10760296231171082 - Supplemental material for Machine Learning to Dynamically Predict In-Hospital Venous Thromboembolism After Inguinal Hernia Surgery: Results From the CHAT-1 Study

Author

Yan, Yi–Dan, Yu, Ze, Ding, Lan-Ping, Zhou, Min, Zhang, Chi, Pan, Mang-Mang, Zhang, Jin-Yuan, Wang, Ze-Yuan, Gao, Fei, Li, Hang-Yu, Zhang, Guang-Yong, Lin, Hou-Wen, Wang, Ming-Gang, and Gu, Zhi–Chun

Subjects
FOS: Clinical medicine, Cardiology, 111599 Pharmacology and Pharmaceutical Sciences not elsewhere classified
Abstract

Supplemental material, sj-docx-1-cat-10.1177_10760296231171082 for Machine Learning to Dynamically Predict In-Hospital Venous Thromboembolism After Inguinal Hernia Surgery: Results From the CHAT-1 Study by Yi–Dan Yan, Ze Yu, Lan-Ping Ding, Min Zhou, Chi Zhang, Mang-Mang Pan, Jin-Yuan Zhang, Ze-Yuan Wang, Fei Gao, Hang-Yu Li, Guang-Yong Zhang, Hou-Wen Lin, Ming-Gang Wang and Zhi–Chun Gu in Clinical and Applied Thrombosis/Hemostasis

Published
2023
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16. A model based on machine learning for the prediction of cyclosporin A trough concentration in Chinese allo-HSCT patients.

Author

Song, Lin, Huang, Chen-Rong, Pan, Shi-Zheng, Zhu, Jian-Guo, Cheng, Zong-Qi, Yu, Xun, Xue, Ling, Xia, Fan, Zhang, Jin-Yuan, Wu, De-Pei, and Miao, Li-Yan

Subjects
MACHINE learning, CYCLOSPORINE, DRUG monitoring, HEMATOPOIETIC stem cell transplantation
Abstract

Cyclosporin A is a calcineurin inhibitor which has a narrow therapeutic window and high interindividual variability. Various population pharmacokinetic models have been reported; however, professional software and technical personnel were needed and the variables of the models were limited. Therefore, the aim of this study was to establish a model based on machine learning to predict CsA trough concentrations in Chinese allo-HSCT patients. A total of 7874 cases of CsA therapeutic drug monitoring data from 2069 allo-HSCT patients were retrospectively included. Sequential forward selection was used to select variable subsets, and eight different algorithms were applied to establish the prediction model. XGBoost exhibited the highest prediction ability. Except for the variables that were identified by previous studies, some rarely reported variables were found, such as norethindrone, WBC, PAB, and hCRP. The prediction accuracy within ±30% of the actual trough concentration was above 0.80, and the predictive ability of the models was demonstrated to be effective in external validation. In this study, models based on machine learning technology were established to predict CsA levels 3–4 days in advance during the early inpatient phase after HSCT. A new perspective for CsA clinical application is provided. [ABSTRACT FROM AUTHOR]

Published
2023
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21. Efficacy and safety of Changfu peritoneal dialysis solution: a multi-center prospective randomized controlled trial

Author

ZHOU, Jian-Hui, NI, Zhao-Hui, MEI, Chang-Lin, YU, Xue-Qing, LIU, Fu-You, MIAO, Li-Ning, LIU, Zhi-Hong, YUAN, Weijie, ZHANG, Ai-Ping, LIN, Hong-Li, CHEN, Meng-Hua, CHEN, Jiang-Hua, ZHANG, Jin-Yuan, HE, Ya-Ni, CHEN, Jian, ZHAO, Jiu-Yang, DING, Xiao-Qiang, LI, Ying, LI, Rong-Shan, XIE, Ru-Juan, LIU, Wen-Hu, XING, Chang-Ying, WANG, Rong, DENG, Yue-Yi, CAO, Xue-Ying, CAI, Guang-Yan, MOU, Shan, MAO, Zhi-Guo, YANG, Xiao, LIU, Hong, SUN, Jing, YU, Yu-Sheng, LIU, Jun, SHI, Shu-Mei, LI, Long-Kai, TIAN, Na, ZHANG, Xiao-Hui, ZHOU, Wei, YANG, Jie, ZHANG, Yong, SUN, Jing-Di, JI, Jun, ZHANG, Tao, YAN, Yan, LIU, Xiao-Gang, WANG, Gang, ZHANG, Li, ZHANG, Hong, LUO, Jian-Hua, and CHEN, Xiang-Mei

Published
2013
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34. The crystal structure of poly[aqua-(μ2-4,4′- bis(imidazolyl)biphenyl-κ2N:N′)-(μ2-3-nitrobenzene-1,2-dicarboxylato-κ2O:O′)]copper (II) hydrate, C26H21N5O8Cu

Author

Li, Gui-Lian, Liu, Meng-Ni, Du, Gao-Jing, and Zhang, Jin-Yuan

Subjects
CRYSTAL structure, COPPER
Abstract

C26H21N5O8Cu, monoclinic, P21/c (no. 14), a = 17.2262(10) Å, b = 7.3474(3) Å, c = 21.1086(11) Å, β = 111.498(6)°, V = 2485.8(2) Å3, Z = 4, Rgt(F) = 0.0629, wRref(F2) = 0.1433, T = 293(2) K. [ABSTRACT FROM AUTHOR]

Published
2022
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38. Prevalence, awareness, and treatment of anemia in Chinese patients with nondialysis chronic kidney disease

Author

Li, Ya, Shi, Hao, Wang, Wei-Ming, Peng, Ai, Jiang, Geng-Ru, Zhang, Jin-Yuan, Ni, Zhao-Hui, He, Li-Qun, Niu, Jian-Ying, Wang, Nian-Song, Mei, Chang-Lin, Xu, Xu-Dong, Guo, Zhi-Yong, Yuan, Wei-Jie, Yan, Hai-Dong, Deng, Yue-Yi, Yu, Chen, Cen, Jun, Zhang, Yun, and Chen, Nan

Subjects
diabetic nephropathy, prevalence, Observational Study, awareness, anemia, chronic kidney disease, Research Article
Abstract

This was the first multicenter, cross-sectional survey to assess the prevalence of anemia, patient awareness, and treatment status in China. Data of patients with chronic kidney disease (CKD; age, 18–75 years; both out- and inpatients) from 25 hospitals in Shanghai, seeking medical treatment at the nephrology department, were collected between July 1, 2012 and August 31, 2012. The prevalence, awareness, and treatment of anemia in patients with nondialysis CKD (ND-CKD) were assessed. Anemia was defined as serum hemoglobin (Hb) levels ≤12 g/dL in women and ≤13 g/dL in men. A total of 2420 patients with ND-CKD were included. Anemia was established in 1246 (51.5%) patients: 639 (51.3%) men and 607 (48.7%) women. The prevalence of anemia increased with advancing CKD stage (χ2trend = 675.14, P

Published
2016

47. An Atomically Precise Au10Ag2 Nanocluster with Red-Near-IR Dual Emission.

Author

Lei, ZhEN, Guan, Zong ‐ Jie, Pei, Xiao ‐ Li, Yuan, Shang ‐ Fu, Wan, Xian ‐ Kai, Zhang, Jin ‐ Yuan, and Wang, Quan ‐ Ming

Subjects
OPTICAL properties of nanocrystals, NANOPARTICLES, PHOSPHINE, LIGANDS (Chemistry), MOLECULAR emission cavity analysis
Abstract

A red-near-IR dual-emissive nanocluster with the composition [Au10Ag2(2-py−C≡C)3(dppy)6](BF4)5 ( 1; 2-py−C≡C is 2-pyridylethynyl, dppy=2-pyridyldiphenylphosphine) has been synthesized. Single-crystal X-ray structural analysis reveals that 1 has a trigonal bipyramidal Au10Ag2 core that contains a planar Au4(2-py−C≡C)3 unit sandwiched by two Au3Ag(dppy)3 motifs. Cluster 1 shows intense red-NIR dual emission in solution. The visible emission originates from metal-to-ligand charge transfer (MLCT) from silver atoms to phosphine ligands in the Au3Ag(dppy)3 motifs, and the intense NIR emission is associated with the participation of 2-pyridylethynyl in the frontier orbitals of the cluster, which is confirmed by a time-dependent density functional theory (TD-DFT) calculation. [ABSTRACT FROM AUTHOR]

Published
2016
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50. A Novel 1.3-µm High T0AlGaInAs/InP Strained-Compensated Multi-Quantum Well Complex-Coupled Distributed Feedback Laser Diode

Author

Chen, Bo, Wang, Wei, Wang, Xiao-Jie, Zhang, Jin-Yuan, and Fan, Zhou

Abstract

A 1.3-µm AlGaInAs/InP buried heterostructure (BH) stripe distributed feedback laser with a novel AlInAs/InP complex-coupled grating grown by low-pressure metalorganic chemical vapor deposition (LP-MOCVD) is proposed and demonstrated. A high characteristic temperature (T0=90 K between 20-80°C) and temperature-insensitive slope efficiency (0.25 dB drop from 20 to 80°C) in 1.3 µm AlGaInAs/InP DFB lasers was obtained by introducing Al(Ga)InAs graded-index separate-confinement heterostructure (GRINSCH) layers and a strained-compensated (SC) multi-quantum well (MQW).

Published
1999
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