Bo Peng
5 Papers
Bo Peng is an academic researcher. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 1, co-authored 1 publications.
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Papers
Circulating tumor DNA predicts response in Chinese patients with relapsed or refractory classical hodgkin lymphoma treated with sintilimab
Yuankai Shi,Hang Su,Yongping Song,Wenqi Jiang,Xiuhua Sun,Wenbin Qian,Wei Zhang,Yuhuan Gao,Zhengming Jin,Jianfeng Zhou,Chuan Jin,Liqun Zou,Lugui Qiu,Wei Li,Jianmin Yang,Ming Hou,Yan Xiong,Hui Zhou,Xinhua Du,Xiong Wang,Bo Peng +20 more
TL;DR: Blood-based biomarker ctDNA could be an informative biomarker for anti-PD-1 immunotherapy in r/r cHL and the mutations of B2M, TNFRSF14 and KDM2B were found to be associated with acquired resistance.
32
TMLP+SRDANN: A domain adaptation method for EEG-based emotion recognition
TL;DR: Zhang et al. as discussed by the authors proposed Transposition Multi-Layer Perceptron (TMLP) and Sample-Reweighted Domain Adaptation Neural Network (SRDANN) in one whole learning framework.
23
Applications and research progress of Traditional Chinese medicine delivered via nasal administration.
Hongping Hou,Yujie Li,Zhiying Xu,Zihui Yu,Bo Peng,Caixia Wang,Wei Li,Wei Liu,Zu-Guang Ye,Guangping Zhang +9 more
- 15 Nov 2022
TL;DR: Wang et al. as discussed by the authors reviewed the development and applications of different nasal preparations of TCM from the aspects of nasal structure, origin, factors affecting absorption and common dosage forms, pharmacodynamics, targeting of nasal delivery and safety.
10
The Role of Connexin Hemichannels in Inflammatory Diseases
TL;DR: It is increasingly clear that CxHC can be induced to open by pathogen-associated molecular patterns, and this review provides an update on the progress in the understanding of Cx HC, with a focus on the role of these channels in inflammatory diseases.
A Novel Tensorial Scheme for EEG-Based Person Identification
TL;DR: Wang et al. as mentioned in this paper proposed a novel and effective tensorial scheme away from the deep learning mainstream, which extracts the effective tensor representation from multichannel EEG at first, then the scheme performs the designed tensorial learning to improve the discriminability of the feature space; and finally, the scheme carries out the devised tensorial measurement in the learned metric space for classification.