Search

Your search keyword '"Gong, Feng"' showing total 2,021 results
Start Over Author "Gong, Feng" Publication Year Range Last 50 years
2,021 results on '"Gong, Feng"'

37. Preparation of silicon carbide ceramic slurry for stereolithography based additive manufacturing

Author

Ye Gaolin, Jiao Yifei, Zhou Peng, Sun Jinxing, Zhu Likuan, Gong Feng, Bai Jiaming, Liu Gang, Yan Ming, and Zhang Rubing

Subjects
stereolithography, silicon carbide, additive manufacturing, properties, Clay industries. Ceramics. Glass, TP785-869
Abstract

Stereolithography-based additive manufacturing of ceramics has received tremendous attention in academic and industrial communities. In order to fabricate silicon carbide (SiC) components with complex shapes by stereolithography, a high SiC loaded ceramic slurry with low viscosity and excellent curing ability is required. However, it is challenging to meet these slurry requirements. In this work, the effects of resin formulation, dispersant, particle size, solid content and ball milling time on the properties of SiC ceramic slurry were systematically studied. The SiC slurries were prepared by using four precursor SiC powders having different particle sizes and modified by high temperature oxidation to reduce its UV absorbance. Additionally, the suitable SiC slurries for stereolithography were prepared by ball milling under appropriate processing parameters, and the geometrically complex SiC green bodies were subsequently fabricated.

Published
2023
Full Text
View/download PDF

38. Hepatocyte apoptosis fragment product cytokeratin-18 M30 level and non-alcoholic steatohepatitis risk diagnosis: an international registry study

Author

Huai Zhang, Rafael S. Rios, Jerome Boursier, Rodolphe Anty, Wah-Kheong Chan, Jacob George, Yusuf Yilmaz, Vincent Wai-Sun Wong, Jiangao Fan, Jean-François Dufour, George Papatheodoridis, Li Chen, Jörn M. Schattenberg, Junping Shi, Liang Xu, Grace Lai-Hung Wong, Naomi F. Lange, Margarita Papatheodoridi, Yuqiang Mi, Yujie Zhou, Christopher D. Byrne, Giovanni Targher, Gong Feng, Minghua Zheng, and Yuanyuan Ji

Subjects
Medicine
Abstract

Abstract. Background:. Liver biopsy for the diagnosis of non-alcoholic steatohepatitis (NASH) is limited by its inherent invasiveness and possible sampling errors. Some studies have shown that cytokeratin-18 (CK-18) concentrations may be useful in diagnosing NASH, but results across studies have been inconsistent. We aimed to identify the utility of CK-18 M30 concentrations as an alternative to liver biopsy for non-invasive identification of NASH. Methods:. Individual data were collected from 14 registry centers on patients with biopsy-proven non-alcoholic fatty liver disease (NAFLD), and in all patients, circulating CK-18 M30 levels were measured. Individuals with a NAFLD activity score (NAS) ≥5 with a score of ≥1 for each of steatosis, ballooning, and lobular inflammation were diagnosed as having definite NASH; individuals with a NAS ≤2 and no fibrosis were diagnosed as having non-alcoholic fatty liver (NAFL). Results:. A total of 2571 participants were screened, and 1008 (153 with NAFL and 855 with NASH) were finally enrolled. Median CK-18 M30 levels were higher in patients with NASH than in those with NAFL (mean difference 177 U/L; standardized mean difference [SMD]: 0.87 [0.69–1.04]). There was an interaction between CK-18 M30 levels and serum alanine aminotransferase, body mass index (BMI), and hypertension (P

Published
2023
Full Text
View/download PDF

47. Automated diagnosis of anterior cruciate ligament via a weighted multi-view network

Author

Feng Li, Penghua Zhai, Chao Yang, Gong Feng, Ji Yang, and Yi Yuan

Subjects
multi-view learning, ACL diagnosis, computer-aided diagnosis, deep learning, magnetic resonance imaging, Biotechnology, TP248.13-248.65
Abstract

Objective: To build a three-dimensional (3D) deep learning-based computer-aided diagnosis (CAD) system and investigate its applicability for automatic detection of anterior cruciate ligament (ACL) of the knee joint in magnetic resonance imaging (MRI).Methods: In this study, we develop a 3D weighted multi-view convolutional neural network by fusing different views of MRI to detect ACL. The network is evaluated on two MRI datasets, the in-house MRI-ACL dataset and the publicly available MRNet-v1.0 dataset. In the MRI-ACL dataset, the retrospective study collects 100 cases, and four views per patient are included. There are 50 ACL patients and 50 normal patients, respectively. The MRNet-v1.0 dataset contains 1,250 cases with three views, of which 208 are ACL patients, and the rest are normal or other abnormal patients.Results: The area under the receiver operating characteristic curve (AUC) of the ACL diagnosis system is 97.00% and 92.86% at the optimal threshold for the MRI-ACL dataset and the MRNet-v1.0 dataset, respectively, indicating a high overall diagnostic accuracy. In comparison, the best AUC of the single-view diagnosis methods are 96.00% (MRI-ACL dataset) and 91.78% (MRNet-v1.0 dataset), and our method improves by about 1.00% and 1.08%. Furthermore, our method also improves by about 1.00% (MRI-ACL dataset) and 0.28% (MRNet-v1.0 dataset) compared with the multi-view network (i.e., MRNet).Conclusion: The presented 3D weighted multi-view network achieves superior AUC in diagnosing ACL, not only in the in-house MRI-ACL dataset but also in the publicly available MRNet-v1.0 dataset, which demonstrates its clinical applicability for the automatic detection of ACL.

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results