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Research
Prof. Dong-Joo Kim's paper accepted in Information Sciences
Author Administrator (IP: *.152.74.116) Date 2019-02-28 15:31 Views 124
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Prof. Dong-Joo Kim's research paper, Automated artifact elimination of physiological signals using a deep belief network: An application for continuously measured arterial blood pressure waveformswas accepted in Information Sciences.

 

Title: Automated artifact elimination of physiological signals using a deep belief network: An application for continuously measured arterial blood pressure waveforms

 

Abstract:

Artifacts in physiological signals acquired during intensive care have the potential to be recognized as critical pathological events and lead to misdiagnosis or mismanagement. Manual artifact removal necessitates significant labor-time intensity and is subject to inter- and intra-observer variability. Various methods have been proposed to automate the task; however, the methods are yet to be validated, possibly due to the diversity of artifact types. Deep belief networks (DBNs) have been shown to be capable of learning generative and discriminative feature extraction models, hence suitable for classifying signals with multiple features. This study proposed a DBN-based model for artifact elimination in pulse waveform signals, which incorporates pulse segmentation, pressure normalization and decision models using DBN, and applied the model to artifact removal in monitoring arterial blood pressure (ABP). When compared with a widely used ABP artifact removal algorithm (signal abnormality index; SAI), the DBN model exhibited significantly higher classification performance (net prediction of optimal DBN = 95.9%, SAI = 84.7%). In particular, DBN exhibited greater sensitivity than SAI for identifying various types of artifacts (motion = 93.6%, biological = 95.4%, cuff inflation = 89.1%, transducer flushing = 97%). The proposed model could significantly enhance the quality of signal analysis, hence may be beneficial for use in continuous patient monitoring in clinical practice.


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Research
Prof. Byoung-Kyong Min's paper published at NeuroImage
Prof. Byoung-Kyong Min's paper published at NeuroImage
Prof. Byoung-Kyong Min's research paper, 'Thalamocortical Inhibitory Dynamics Support Conscious Perception' was publishsed at NeuroImage. Link to the publication: https://doi.org/10.1016/j.neuroimage.2020.117066 Title: Thalamocortical Inhibitory Dynamics Support Conscious Perception Abstract:Whether thalamocortical interactions play a decisive role in conscious perception remains an open question. We presented rapid red/g…

2020-06-15

Prof. Jeehyun Kwag's paper accepted in Chaos
Prof. Jeehyun Kwag's paper accepted in Chaos
Prof. Jeehyun Kwag's research paper, 'Distinct subtypes of inhibitory interneurons differentially promote the propagation of rate and temporal codes in the feedforward neural network' was accepted in Chaos.  link to the publication: https://aip.scitation.org/doi/full/10.1063/1.5134765Title: Distinct subtypes of inhibitory interneurons differentially promote the propagation of rate and temporal codes in the feedforward neu…

2020-05-29

Prof. Jeehyun Kwag's paper accepted in Science Advances
Prof. Jeehyun Kwag's paper accepted in Science Advances
Prof. Jeehyun Kwag's research paper, 'Distinct roles of parvalbumin and somatostatin interneurons in gating the synchronization of spike times in the neocortex'  was accepted in Science Advances.  Publication Link: https://advances.sciencemag.org/content/6/17/eaay5333/Title: Distinct roles of parvalbumin and somatostatin interneurons in gating the synchronization of spike times in the neocortexAbstract: Synchron…

2020-04-23

Prof. Byoung-Kyong Min's paper accepted in Trends in Biotechnology
Prof. Byoung-Kyong Min's paper accepted in Trends in Biotechnology
Prof. Byoung-Kyong Min's research paper, 'New Cognitive Neurotechnology Facilitates Studies of Cortical-Subcortical Interactions' was accepted in Trends in Biotechnology. Title: New Cognitive Neurotechnology Facilitates Studies of Cortical-Subcortical Interactions Abstract:Most of the studies employing neuroimaging have focused on cortical and subcortical signals individually to obtain neurophysiological signatures of cognitiv…

2020-03-09

Prof. Jeehyun Kwag's paper accepted in Brain Structure and Function
Prof. Jeehyun Kwag's paper accepted in Brain Structure and Function
Prof. Jeehyun Kwag's research paper, 'Dissociation of Somatostatin and Parvalbumin Interneurons Circuit Dysfunctions Underlying Hippocampal Theta and Gamma Oscillations impaired by Amyloid β Oligomers in Vivo' was accepted in Brain Structure and Function. Publication Link: https://link.springer.com/article/10.1007/s00429-020-02044-3Title: Dissociation of somatostatin and parvalbumin interneurons circuit dysfunctions underlyin…

2020-03-02

Prof. Jeehyun Kwag's paper accepted in BMC Biology
Prof. Jeehyun Kwag's paper accepted in BMC Biology
Prof. Jeehyun Kwag's research paper, 'Optogenetic activation of parvalbumin and somatostatin interneurons selectively restores theta-nested gamma oscillations and oscillation-induced spike timing-dependent long-term potentiation impaired by amyloid β oligomers' was accepted in BMC Biology. Title: Optogenetic activation of parvalbumin and somatostatin interneurons selectively restores theta-nested gamma oscillations and oscillation…

2020-03-02

Prof. Heung-Il Suk's paper accepted in NeuroImage
Prof. Heung-Il Suk's paper accepted in NeuroImage
Prof. Heung-Il Suk's research paper, 'Toward an Interpretable Alzheimer's Disease Diagnostic Model with Regional Abnormality Representation via Deep Learning' was accepted in NeuroImage.  Title: Toward an Interpretable Alzheimer's Disease Diagnostic Model with Regional Abnormality Representation via Deep Learning  Abstract: In this paper, we propose a novel method for magnetic resonance imaging based Alzheimer's disease (…

2019-08-20

Prof.Jae-Ho Han’s paper accepted in IEEE Transactions on Image Processing
Prof.Jae-Ho Han’s paper accepted in IEEE Transactions on Image Processing
Prof. Jae-Ho Han’s new research on `Deep Neural Network Regression for Automated Retinal Layer Segmentation in Optical Coherence Tomography Images` was accepted in IEEE Transactions on Image Processing.  Title: Deep Neural Network Regression for Automated Retinal Layer Segmentation in Optical Coherence Tomography ImagesAbstract: Segmenting the retinal layers in optical coherence tomography (OCT) images helps to quantify the …

2019-07-24

Prof. Seong-Whan Lee's paper accepted in IEEE Transactions on Intelligent Transportation Systems
Prof. Seong-Whan Lee's paper accepted in IEEE Transactions on Intelligent Transp…
Prof. Seong-Whan Lee's new research, Coarse-to-Fine Deep Learning of Continuous Pedestrian Orientation Based on Spatial Co-occurrence Feature was accepted in IEEE Transactions on Intelligent Transportation Systems. Title: 'Coarse-to-Fine Deep Learning of Continuous Pedestrian Orientation Based on Spatial Co-occurrence Feature Abstract: The continuous orientation estimation of a moving pedestrian is a crucial issue in auto…

2019-05-02

Prof. Heung-Il Suk's paper accepted in Neural Networks
Prof. Heung-Il Suk's paper accepted in Neural Networks
Prof. Heung-Il Suk's research paper, 'Multi-Scale Gradual Integration CNN for False Positive Reduction in Pulmonary Nodule Detection' was accepted in Neural Networks.   Title: Multi-Scale Gradual Integration CNN for False Positive Reduction in Pulmonary Nodule Detection Abstract: Lung cancer is a global and dangerous disease, and its early detection is crucial for reducing the risks of mortality. In this regard, it has been o…

2019-03-07

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