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Ning Liu,WuHan Yu,Mengjiao Sun,Wenjing Zhang,Dan Zhou,Jing Sun,ManXia Wang 대한신경과학회 2023 Journal of Clinical Neurology Vol.19 No.4
Background and Purpose A systematic review and meta-analysis was performed of the outcome of Coronavirus disease 2019 (COVID-19) infection in patients with multiple sclerosis (MS) who received disease-modifying therapies (DMTs). Methods Relevant studies published before November 2022 in the PubMed, Cochrane Library, Chinese National Knowledge Infrastructure, and Web of Science databases were retrieved using the following search expression: (“multiple sclerosis” OR “MS”) AND (“DMT” OR “disease modifying therapies”) AND (“COVID-19”). Two authors independently screened the articles and extracted the data. Qualitative analyses and a meta-analysis constituted 22 of the 794 retrieved articles. Differences in the hospitalization and mortality rates were used as the main measures of efficacy, and the meta-analysis was performed using RevMan software. Results 22 clinical trials were selected. The hospitalization rate was lower in the 3,216 patients who received DMTs than in the 774 patients who did not receive any treatment, with a moderate effect size of 0.43 (p<0.00001). The mortality rate was also lower among patients with MS treated using DMTs than in controls (odds ratio [OR]=0.19, 95% confidence interval [CI]=0.13–0.27, p<0.00001). The hospitalization rates for COVID-19 infection in patients with MS treated with anti-CD20 therapy also increased markedly (OR=3.32, 95% CI=2.63–4.20, p<0.00001). However, there was no significant difference between patients with MS who did and did not receive DMTs. Conclusions In summary, the application of DMTs was found to be valuable for patients with MS infected with COVID-19. However, more clinical studies are needed to determine the use of anti-CD20 drugs in patients with MS during the COVID-19 pandemic.
Seafloor Classification Based on the Texture Analysis of Sonar Images Using the Gabor Wavelet
Sun, Ning,Shim, Tae-Bo The Acoustical Society of Korea 2008 韓國音響學會誌 Vol.27 No.e3
In the process of the sonar image textures produced, the orientation and scale factors are very significant. However, most of the related methods ignore the directional information and scale invariance or just pay attention to one of them. To overcome this problem, we apply Gabor wavelet to extract the features of sonar images, which combine the advantages of both the Gabor filter and traditional wavelet function. The mother wavelet is designed with constrained parameters and the optimal parameters will be selected at each orientation, with the help of bandwidth parameters based on the Fisher criterion. The Gabor wavelet can have the properties of both multi-scale and multi-orientation. Based on our experiment, this method is more appropriate than traditional wavelet or single Gabor filter as it provides the better discrimination of the textures and improves the recognition rate effectively. Meanwhile, comparing with other fusion methods, it can reduce the complexity and improve the calculation efficiency.
( Ning Sun Hang ),( Guo Jixin Liu ),( Guang Han ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.9
Most available methods of facial gender recognition work well under a constrained situation, but the performances of these methods have decreased significantly when they are implemented under unconstrained environments. In this paper, a method via low-rank and collaborative representation is proposed for facial gender recognition in the wild. Firstly, the low-rank decomposition is applied to the face image to minimize the negative effect caused by various corruptions and dynamical illuminations in an unconstrained environment. And, we employ the collaborative representation to be as the classifier, which using the much weaker l2-norm sparsity constraint to achieve similar classification results but with significantly lower complexity. The proposed method combines the low-rank and collaborative representation to an organic whole to solve the task of facial gender recognition under unconstrained environments. Extensive experiments on three benchmarks including AR, CAS-PERL and YouTube are conducted to show the effectiveness of the proposed method. Compared with several state-of-the-art algorithms, our method has overwhelming superiority in the aspects of accuracy and robustness.
Classification of Seabed Physiognomy Based on Side Scan Sonar Images
Sun, Ning,Shim, Tae-Bo The Acoustical Society of Korea 2007 韓國音響學會誌 Vol.26 No.e3
As the exploration of the seabed is extended ever further, automated recognition and classification of sonar images become increasingly important. However, most of the methods ignore the directional information and its effect on the image textures produced. To deal with this problem, we apply 2D Gabor filters to extract the features of sonar images. The filters are designed with constrained parameters to reduce the complexity and to improve the calculation efficiency. Meanwhile, at each orientation, the optimal Gabor filter parameters will be selected with the help of bandwidth parameters based on the Fisher criterion. This method can overcome some disadvantages of the traditional approaches of extracting texture features, and improve the recognition rate effectively.