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1.
Ieee Transactions on Molecular Biological and Multi-Scale Communications ; 8(4):239-248, 2022.
Article in English | Web of Science | ID: covidwho-2308181

ABSTRACT

The current ongoing COVID-19 pandemic caused by the SARS-CoV-2 virus, has severely affected our daily life routines and behavior patterns. According to the World Health Organization, there have been 93 million confirmed cases with more than 1.99 million confirmed death around 235 Countries, areas or territories until 15 January 2021, 11:00 GMT+11. People who are affected with COVID-19 have different symptoms from people to people. When large amounts of patients are affected with COVID-19, it is important to quickly identify the health conditions of patients based on the basic information and symptoms of patients. Then the hospital can arrange reasonable medical resources for different patients. However, existing work has a low recall of 15.7% for survival predictions based on the basic information of patients (i.e., false positive rate (FPR) with 84.3%, FPR: actually survival but predicted as died). There is much room for improvement when using machine learning-based techniques for COVID-19 prediction. In this paper, we propose DeCoP to train a classifier to predict the survival of COVID-19 patients with high recall and F1 score. DeCoP is a deep learning (DL)-based scheme of Bidirectional Long Short-Term Memory (BiLSTM) along with Fuzzy-based Information Decomposition (FID) to predict the survival of patients. First of all, we apply FID oversampling to redistribute the training data of the Open COVID-19 Data Working Group. Then, we employ BiLSTM to learn the high-level feature representations from the redistributed dataset. After that, the high-level feature vector will be used to train the prediction model. Experimental results show that our proposed scheme achieves outstanding performances. Precisely, the improvement achieves about 19% and 18% in terms of recall and F1-measure.

2.
Discovery Medicine ; 31(162):7-14, 2021.
Article in English | Web of Science | ID: covidwho-1762440

ABSTRACT

In late December 2019, COVID-19 was first identified in Wuhan, China and resulted in a formidable outbreak in provinces and cities in China that became a pandemic. The outbreak likely began as several cases caused by probable zoonotic transmission, followed by human-to-human transmission via droplets or contact with infected bodily fluids or contaminated items. COVID-19 mainly affects the lower respiratory tract and manifests as pneumonia in human, and severely affected patients may have multiple organ dysfunction syndrome. Despite recent progress in vaccine development, the management of multiple organ failure caused by immune injury is mainly supportive. COVID-19 is more contagious than SARS and MERS, although it has a lower mortality rate. The 2019 outbreak of COVID-19 has been classified by the WHO as a Public Health Emergency of International Concern, which has drawn attention to the challenge of the disease and caused questioning of scientific strategies for preventing infection and improving clinical outcomes. This article reviews the latest developments on transmission and clinical management and control of COVID-19 infection.

3.
Chinese Automation Congress (CAC) ; : 7550-7554, 2020.
Article in English | Web of Science | ID: covidwho-1398270

ABSTRACT

Aiming at the prevention and control of multi-group epidemics, the dynamic model of disease transmission is established, and an optimal delay and isolation strategy is proposed. The control variables in the model represent the strength of various measures taken to block and isolate contact between groups. The optimal control problem is solved by Pontryagin maximum principle and the corresponding numerical iterative algorithm is given. The results show that the delay and isolation control strategy can effectively control the epidemic of infectious diseases while minimizing the cost of infectious diseases. The outbreak of the COVID-19 in 2020 is a serious threat to people's lives and health. It is because of the timely adoption of delay and isolation control strategy of "early detection and early isolation" and "joint-prevention and joint-control", China took the lead in the fight against the epidemic situation and made an example for the whole world.

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