Zobrazeno 1 - 10
of 92
pro vyhledávání: '"Xiuquan Du"'
Publikováno v:
Diagnostics, Vol 13, Iss 11, p 1971 (2023)
Deep learning, with continuous development, has achieved relatively good results in the field of left atrial segmentation, and numerous semi-supervised methods in this field have been implemented based on consistency regularization to obtain high-per
Externí odkaz:
https://doaj.org/article/4e5dc01983e144e3adc03bf38fcdff4a
Publikováno v:
PeerJ, Vol 9, p e11262 (2021)
DNA-binding proteins (DBPs) play pivotal roles in many biological functions such as alternative splicing, RNA editing, and methylation. Many traditional machine learning (ML) methods and deep learning (DL) methods have been proposed to predict DBPs.
Externí odkaz:
https://doaj.org/article/3051923860474bee876dd2404a3830ae
Publikováno v:
IEEE Journal of Translational Engineering in Health and Medicine, Vol 7, Pp 1-10 (2019)
Accurate segmentation of cardiac bi-ventricle (CBV) from magnetic resonance (MR) images has a great significance to analyze and evaluate the function of the cardiovascular system. However, the complex structure of CBV image makes fully automatic segm
Externí odkaz:
https://doaj.org/article/cabaabe8f0e44201a979d2e8c37353e3
Publikováno v:
IEEE Access, Vol 7, Pp 23537-23548 (2019)
Oversampling is an efficient technique in dealing with class-imbalance problem. It addresses the problem by reduplicating or generating the minority class samples to balance the distribution between the samples of the majority and the minority class.
Externí odkaz:
https://doaj.org/article/1a55d3970ca44b89aa96f6b730fbdfff
Publikováno v:
IEEE Journal of Translational Engineering in Health and Medicine, Vol 6, Pp 1-10 (2018)
Accurate segmentation of right ventricle (RV) from cardiac magnetic resonance (MR) images can help a doctor to robustly quantify the clinical indices including ejection fraction. In this paper, we develop one regression convolutional neural network (
Externí odkaz:
https://doaj.org/article/09bf2c9af0f0436b8cff5db560707138
Autor:
Xiuquan Du, Weiwei Zhang, Heye Zhang, Jun Chen, Yanping Zhang, James Claude Warrington, Gary Brahm, Shuo Li
Publikováno v:
IEEE Access, Vol 6, Pp 3828-3838 (2018)
Cardiac bi-ventricle segmentation can help physicians to obtain clinical indices, such as mass and volume of left ventricle (LV) and right ventricle (RV). In this paper, we propose a regression segmentation framework to delineate boundaries of bi-ven
Externí odkaz:
https://doaj.org/article/f96f42e8008b4059abb860630e5ae55a
Publikováno v:
IEEE Access, Vol 6, Pp 32958-32978 (2018)
Splice sites prediction and interpretation are crucial to the understanding of complicated mechanisms underlying gene transcriptional regulation. Although existing computational approaches can classify true/false splice sites, the performance mostly
Externí odkaz:
https://doaj.org/article/a694459909b347999415ff4cadf104af
Publikováno v:
PeerJ, Vol 7, p e7126 (2019)
Protein–protein interactions are closely relevant to protein function and drug discovery. Hence, accurately identifying protein–protein interactions will help us to understand the underlying molecular mechanisms and significantly facilitate the d
Externí odkaz:
https://doaj.org/article/8486dafb0ef043ee9f01d289adc09aab
Autor:
Guotao Liu, Yanping Zhang, Zhenghui Hu, Xiuquan Du, Wanqing Wu, Chenchu Xu, Xiangyang Wang, Shuo Li
Publikováno v:
Parkinson's Disease, Vol 2017 (2017)
In this study, a new combination scheme has been proposed for detecting Parkinson’s disease (PD) from electroencephalogram (EEG) signal recorded from normal subjects and PD patients. The scheme is based on discrete wavelet transform (DWT), sample e
Externí odkaz:
https://doaj.org/article/54b4e8bf63c94286a508be6f2a94a90b
Publikováno v:
International Journal of Molecular Sciences, Vol 15, Iss 7, Pp 12731-12749 (2014)
Protein–protein interactions (PPIs) play key roles in most cellular processes, such as cell metabolism, immune response, endocrine function, DNA replication, and transcription regulation. PPI prediction is one of the most challenging problems in fu
Externí odkaz:
https://doaj.org/article/e4b76a7c5cdf41fb80d9c4af2af1e32c