Hongmei Zhang

Dr. Hongmei Zhang

orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 May 2019 in Advanced Functional Materials
Verified
Journal Article
Closed access
PDF file
JDJun Deng
Jun Deng
YTYingying Tang
Yingying Tang
QZQing Zhang
Qing Zhang
CWChao Wang
Chao Wang
MLMin Liao
Min Liao
HTHong Tan
Hong Tan

1 May 2021 in Annals of Translational Medicine
Verified
Journal Article
Open access
PDF file
LZLiwen Zheng
Liwen Zheng
HWHaolin Wang
Haolin Wang
LMLi Mei
Li Mei
QCQiuman Chen
Qiuman Chen
YZYuxin Zhang
Yuxin Zhang
HZHongmei Zhang
Hongmei Zhang
Background: An accurate diagnosis of deep caries and pulpitis on periapical radiographs is a clinical challenge. Methods: A total of 844 radiographs were included in this study. Of the 844, 717 (85%) were used for training and 127 (15%) were used for testing the three convolutional neural networks (CNNs) (VGG19, Inception V3, and ResNet18). The performance [accuracy, precision, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC)] of the CNNs were evaluated and compared. The CNN model with the best performance was further integrated with clinical parameters to see whether multi-modal CNN could provide an enhanced performance. The Gradient-weighted Class Activation Mapping (Grad-CAM) technique illustrates what image feature was the most important for the CNNs. Results: The CNN of ResNet18 demonstrated the best performance [accuracy =0.82, 95% confidence interval (CI): 0.80–0.84; precision =0.81, 95% CI: 0.73–0.89; sensitivity =0.85, 95% CI: 0.79–0.91; specificity =0.82, 95% CI: 0.76–0.88; and AUC =0.89, 95% CI: 0.86–0.92], compared with VGG19 and Inception V3 as well as the comparator dentists. Therefore, ResNet18 was chosen to integrate with clinical parameters to produce the multi-modal CNN of ResNet18 + C, which showed a significantly enhanced performance (accuracy =0.86, 95% CI: 0.84–0.88; precision =0.85, 95% CI: 0.76–0.94; sensitivity =0.89, 95% CI: 0.83–0.95; specificity =0.86, 95% CI: 0.79–0.93; and AUC =0.94, 95% CI: 0.91–0.97). Conclusions: The CNN of ResNet18 showed good performance (accuracy, precision, sensitivity, specificity, and AUC) for the diagnosis of deep caries and pulpitis. The multi-modal CNN of ResNet18 + C (ResNet18 integrated with clinical parameters) demonstrated a significantly enhanced performance, with promising potential for the diagnosis of deep caries and pulpitis.

17 October 2020 in Genes & Diseases
Verified
Journal Article
Open access
XHXia Huang
Xia Huang
QCQiuman Chen
Qiuman Chen
WLWenping Luo
Wenping Luo
MPMikhail Pakvasa
Mikhail Pakvasa
YZYuxin Zhang
Yuxin Zhang
HZHongmei Zhang
Hongmei Zhang
SATB2 (special AT-rich sequence-binding protein 2) is a member of the special AT-rich binding protein family. As a transcription regulator, SATB2 mainly integrates higher-order chromatin organization. SATB2 expression appears to be tissue- and stage-specific, and is governed by several cellular signaling molecules and mediators. Expressed in branchial arches and osteoblast-lineage cells, SATB2 plays a significant role in craniofacial pattern and skeleton development. In addition to regulating osteogenic differentiation, SATB2 also displays versatile functions in neural development and cancer progression. As an osteoinductive factor, SATB2 holds great promise in improving bone regeneration toward bone defect repair. In this review, we have summarized our current understanding of the physiological and pathological functions of SATB2 in craniofacial and skeleton development, neurogenesis, tumorigenesis and regenerative medicine.

29 May 2024 in Journal of Materials Chemistry B
Verified
Journal Article
Closed access
PDF file
SRShidian Ran
Shidian Ran
LXLinyu Xue
Linyu Xue
XWXiaorui Wei
Xiaorui Wei
JHJindie Huang
Jindie Huang
XYXingrui Yan
Xingrui Yan
MGMengqin Gu
Mengqin Gu
Schematic illustration of injectable hydrogels in periodontitis treatment.

17 September 2023 in Advanced Healthcare Materials
Verified
Journal Article
Closed access
DLDize Li
Dize Li
XTXi Tan
Xi Tan
LZLiwen Zheng
Liwen Zheng
HTHan Tang
Han Tang
SHShanshan Hu
Shanshan Hu
HZHongmei Zhang
Hongmei Zhang

17 October 2023 in Biomaterials
Verified
Journal Article
Closed access
MLMingzheng Li
Mingzheng Li
DLDan Li
Dan Li
YJYucan Jiang
Yucan Jiang
PHPing He
Ping He
YLYeming Li
Yeming Li
HYHuipin Yuan
Huipin Yuan