53 results match your criteria Applied Soft Computing[Journal]

HSSAGA: Designation and scheduling of nurses for taking care of COVID-19 patients using novel method of Hybrid Salp Swarm Algorithm and Genetic Algorithm.

Appl Soft Comput 2021 Sep 30;108:107449. Epub 2021 Apr 30.

Department of Industrial Engineering, Urmia University of Technology (UUT), P.O. Box: 57166-419, Urmia, Iran.

The COVID-19 pandemic is viewed as the most basic worldwide disaster that humankind has observed since the second World War. There is no report of any clinically endorsed antiviral medications or antibodies that are successful against COVID-19. It has quickly spread everywhere, presenting tremendous well-being, financial, ecological, and social difficulties to the whole human populace. Read More

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September 2021

Federated learning for COVID-19 screening from Chest X-ray images.

Appl Soft Comput 2021 Jul 20;106:107330. Epub 2021 Mar 20.

Department of Software, Sejong University, Seoul 143-747, Republic of Korea.

Today, the whole world is facing a great medical disaster that affects the health and lives of the people: the COVID-19 disease, colloquially known as the Corona virus. Deep learning is an effective means to assist radiologists to analyze the vast amount of chest X-ray images, which can potentially have a substantial role in streamlining and accelerating the diagnosis of COVID-19. Such techniques involve large datasets for training and all such data must be centralized in order to be processed. Read More

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A novel classifier architecture based on deep neural network for COVID-19 detection using laboratory findings.

Appl Soft Comput 2021 Jul 19;106:107329. Epub 2021 Mar 19.

Department of Electrical and Electronics Engineering, Sivas Cumhuriyet University, 58140, Sivas, Turkey.

Unfortunately, Coronavirus disease 2019 (COVID-19) is spreading rapidly all over the world. Along with causing many deaths, it has substantially affected the social life, economics, and infrastructure worldwide in a negative manner. Therefore, it is very important to be able to diagnose the COVID-19 quickly and correctly. Read More

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A new approach for computer-aided detection of coronavirus (COVID-19) from CT and X-ray images using machine learning methods.

Ahmet Saygılı

Appl Soft Comput 2021 Jul 17;105:107323. Epub 2021 Mar 17.

Department of Computer Engineering, Çorlu Faculty of Engineering, Tekirdağ Namık Kemal University, Tekirdağ, Turkey.

The COVID-19 outbreak has been causing a global health crisis since December 2019. Due to this virus declared by the World Health Organization as a pandemic, the health authorities of the countries are constantly trying to reduce the spread rate of the virus by emphasizing the rules of masks, social distance, and hygiene. COVID-19 is highly contagious and spreads rapidly globally and early detection is of paramount importance. Read More

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Supply chain design to tackle coronavirus pandemic crisis by tourism management.

Appl Soft Comput 2021 Jun 20;104:107217. Epub 2021 Feb 20.

Department of Industrial Engineering, Babol Noshirvani University of Technology, Babol, Iran.

The rapid growth of the COVID-19 pandemic in the world and the importance of controlling it in all regions have made managing this crisis a great challenge for all countries. In addition to imposing various monetary costs on countries, this pandemic has left many serious damages and casualties. Proper control of this crisis will provide better medical services. Read More

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A computational tool for trend analysis and forecast of the COVID-19 pandemic.

Appl Soft Comput 2021 Jul 10;105:107289. Epub 2021 Mar 10.

Institute of Science and Technology (ICT), Federal University of Sao Paulo (UNIFESP), Rua Talim, 330, São José dos Campos, SP, Brazil.

Purpose: This paper proposes a methodology and a computational tool to study the COVID-19 pandemic throughout the world and to perform a trend analysis to assess its local dynamics.

Methods: Mathematical functions are employed to describe the number of cases and demises in each region and to predict their final numbers, as well as the dates of maximum daily occurrences and the local stabilization date. The model parameters are calibrated using a computational methodology for numerical optimization. Read More

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Mediative fuzzy logic mathematical model: A contradictory management prediction in COVID-19 pandemic.

Appl Soft Comput 2021 Jul 9;105:107285. Epub 2021 Mar 9.

Department of Mathematics, Indira Gandhi National Tribal University, Lalpur, Amarkantak, Anuppur, Madhya Pradesh 484 887, India.

This paper presents a model based on mediative fuzzy logic in this COVID-19 pandemic. COVID-19 (novel coronavirus respiratory disease) has become a pandemic now and the whole world has been affected by this disease. Different methodologies and many prediction techniques based on various models have been developed so far. Read More

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A causal framework to determine the effectiveness of dynamic quarantine policy to mitigate COVID-19.

Appl Soft Comput 2021 Jun 2;104:107241. Epub 2021 Mar 2.

Robert Morris University, 6001 University Blvd Moon Township, PA 15108, United States of America.

Since the start of the pandemic caused by the novel coronavirus, COVID-19, more than 106 million people have been infected and global deaths have surpassed 2.4 million. In Chile, the government restricted the activities and movement of people, organizations, and companies, under the concept of across municipalities for a predefined period of time. Read More

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Automated Detection of Covid-19 from Chest X-ray scans using an optimized CNN architecture.

Appl Soft Comput 2021 Jun 24;104:107238. Epub 2021 Feb 24.

Department of Electronics and Communication Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, India.

The novel coronavirus termed as covid-19 has taken the world by its crutches affecting innumerable lives with devastating impact on the global economy and public health. One of the major ways to control the spread of this disease is identification in the initial stage, so that isolation and treatment could be initiated. Due to the lack of automated auxiliary diagnostic medical tools, availability of lesser sensitivity testing kits, and limited availability of healthcare professionals, the pandemic has spread like wildfire across the world. Read More

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Utilizing IoT to design a relief supply chain network for the SARS-COV-2 pandemic.

Appl Soft Comput 2021 Jun 24;104:107210. Epub 2021 Feb 24.

Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Puebla, Mexico.

The current universally challenging SARS-COV-2 pandemic has transcended all the social, logical, economic, and mortal boundaries regarding global operations. Although myriad global societies tried to address this issue, most of the employed efforts seem superficial and failed to deal with the problem, especially in the healthcare sector. On the other hand, the Internet of Things (IoT) has enabled healthcare system for both better understanding of the patient's condition and appropriate monitoring in a remote fashion. Read More

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Expeditious COVID-19 similarity measure tool based on consolidated SCA algorithm with mutation and opposition operators.

Mohamed Issa

Appl Soft Comput 2021 Jun 20;104:107197. Epub 2021 Feb 20.

Computer and Systems Department, Faculty of Engineering, Zagazig University, Zagazig, Egypt.

COVID-19 is a global pandemic that aroused the interest of scientists to prevent it and design a drug for it. Nowadays, presenting intelligent biological data analysis tools at a low cost is important to analyze the biological structure of COVID-19. The global alignment algorithm is one of the important bioinformatics tools that measure the most accurate similarity between a pair of biological sequences. Read More

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CoVNet-19: A Deep Learning model for the detection and analysis of COVID-19 patients.

Appl Soft Comput 2021 Jun 15;104:107184. Epub 2021 Feb 15.

Big Data Analytics and Web Intelligence Laboratory, Department of Computer Science, Delhi Technological University, New Delhi, India.

Background: The ongoing fight with Novel Corona Virus, getting quick treatment, and rapid diagnosis reports have become an act of high priority. With millions getting infected daily and a fatality rate of 2%, we made it our motive to contribute a little to solve this real-world problem by accomplishing a significant and substantial method for diagnosing COVID-19 patients.

Aim: The Exponential growth of COVID-19 cases worldwide has severely affected the health care system of highly populated countries due to proportionally a smaller number of medical practitioners, testing kits, and other resources, thus becoming essential to identify the infected people. Read More

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Forecasting the dynamics of cumulative COVID-19 cases (confirmed, recovered and deaths) for top-16 countries using statistical machine learning models: Auto-Regressive Integrated Moving Average (ARIMA) and Seasonal Auto-Regressive Integrated Moving Average (SARIMA).

Appl Soft Comput 2021 May 8;103:107161. Epub 2021 Feb 8.

Department of Chemical and Biological Engineering, South Dakota School of Mines and Technology, Rapid City, SD 57701, USA.

Most countries are reopening or considering lifting the stringent prevention policies such as lockdowns, consequently, daily coronavirus disease (COVID-19) cases (confirmed, recovered and deaths) are increasing significantly. As of July 25th, there are 16.5 million global cumulative confirmed cases, 9. Read More

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DeepCoroNet: A deep LSTM approach for automated detection of COVID-19 cases from chest X-ray images.

Fatih Demir

Appl Soft Comput 2021 May 8;103:107160. Epub 2021 Feb 8.

Firat University, Technology Faculty, Electrical-Electronics Engineering Department, Elazig, Turkey.

The new coronavirus, known as COVID-19, first emerged in Wuhan, China, and since then has been transmitted to the whole world. Around 34 million people have been infected with COVID-19 virus so far, and nearly 1 million have died as a result of the virus. Resource shortages such as test kits and ventilator have arisen in many countries as the number of cases have increased beyond the control. Read More

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An extended fuzzy decision-making framework using hesitant fuzzy sets for the drug selection to treat the mild symptoms of Coronavirus Disease 2019 (COVID-19).

Appl Soft Comput 2021 May 5;103:107155. Epub 2021 Feb 5.

Department of Mathematics, NIT, Durgapur, WB, India.

The whole world is presently under threat from Coronavirus Disease 2019 (COVID-19), a new disease spread by a virus of the corona family, called a novel coronavirus. To date, the cases due to this disease are increasing exponentially, but there is no vaccine of COVID-19 available commercially. However, several antiviral therapies are used to treat the mild symptoms of COVID-19 disease. Read More

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A consensus model to manage the non-cooperative behaviors of individuals in uncertain group decision making problems during the COVID-19 outbreak.

Appl Soft Comput 2021 Feb 9;99:106879. Epub 2020 Nov 9.

Business School, Sichuan University, Chengdu 610064, China.

The COVID-19 pandemic has brought lots of losses to the global economy. Within the context of COVID-19 outbreak, many emergency decision-making problems with uncertain information arose and a number of individuals were involved to solve such complicated problems. For instance, the selection of the first entry point to China is important for oversea flights during the epidemic outbreak given that reducing imported virus from abroad becomes the top priority of China since China has achieved remarkable achievements regarding the epidemic control. Read More

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February 2021

Automated medical diagnosis of COVID-19 through EfficientNet convolutional neural network.

Appl Soft Comput 2020 Nov 29;96:106691. Epub 2020 Aug 29.

Department of Signal Theory and Communications, and Telematics Engineering University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain.

COVID-19 infection was reported in December 2019 at Wuhan, China. This virus critically affects several countries such as the USA, Brazil, India and Italy. Numerous research units are working at their higher level of effort to develop novel methods to prevent and control this pandemic scenario. Read More

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November 2020

Topic detection and sentiment analysis in Twitter content related to COVID-19 from Brazil and the USA.

Appl Soft Comput 2021 Mar 26;101:107057. Epub 2020 Dec 26.

Institute of Science and Technology, Federal University of Sao Paulo, São José dos Campos, São Paulo, 12247-014, Brazil.

Twitter is a social media platform with more than 500 million users worldwide. It has become a tool for spreading the news, discussing ideas and comments on world events. Twitter is also an important source of health-related information, given the amount of news, opinions and information that is shared by both citizens and official sources. Read More

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COVID-19 X-ray images classification based on enhanced fractional-order cuckoo search optimizer using heavy-tailed distributions.

Appl Soft Comput 2021 Mar 24;101:107052. Epub 2020 Dec 24.

Department of Computer, Damietta University, Damietta 34517, Egypt.

Classification of COVID-19 X-ray images to determine the patient's health condition is a critical issue these days since X-ray images provide more information about the patient's lung status. To determine the COVID-19 case from other normal and abnormal cases, this work proposes an alternative method that extracted the informative features from X-ray images, leveraging on a new feature selection method to determine the relevant features. As such, an enhanced cuckoo search optimization algorithm (CS) is proposed using fractional-order calculus (FO) and four different heavy-tailed distributions in place of the Lévy flight to strengthen the algorithm performance during dealing with COVID-19 multi-class classification optimization task. Read More

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Real-time measurement of the uncertain epidemiological appearances of COVID-19 infections.

Appl Soft Comput 2021 Mar 25;101:107039. Epub 2020 Dec 25.

Universidad Internacional de La Rioja, Logroño, Spain.

Virus diseases are a continued threat to human health in both community and healthcare settings. The current virus disease COVID-19 outbreak raises an unparalleled public health issue for the world at large. Wuhan is the city in China from where this virus came first and, after some time the whole world was affected by this severe disease. Read More

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Mitigating the risk of infection spread in manual order picking operations: A multi-objective approach.

Appl Soft Comput 2021 Mar 30;100:106953. Epub 2020 Nov 30.

Department of Analytics and Information Systems, College of Business, Ohio University, OH, 45701, USA.

In the aftermath of the COVID-19 pandemic, supply chains experienced an unprecedented challenge to fulfill consumers' demand. As a vital operational component, manual order picking operations are highly prone to infection spread among the workers, and thus, susceptible to interruption. This study revisits the well-known order batching problem by considering a new overlap objective that measures the time pickers work in close vicinity of each other and acts as a proxy of infection spread risk. Read More

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Drug repositioning based on similarity constrained probabilistic matrix factorization: COVID-19 as a case study.

Appl Soft Comput 2021 May 23;103:107135. Epub 2021 Jan 23.

College of Computer Science and Electronic Engineering, Hunan University, Changsha, Hunan, 410082, China.

The novel coronavirus disease 2019 (COVID-19) pandemic has caused a massive health crisis worldwide and upended the global economy. However, vaccines and traditional drug discovery for COVID-19 cost too much in terms of time, manpower, and money. Drug repurposing becomes one of the promising treatment strategies amid the COVID-19 crisis. Read More

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Multi-criterion Intelligent Decision Support system for COVID-19.

Appl Soft Comput 2021 Mar 29;101:107056. Epub 2020 Dec 29.

Department of Computer Science & Engineering, NIT Delhi, India.

COVID-19 is a buzz word nowadays. The deadly virus that started in China has spread worldwide. The fundamental principle is "if the disease can travel faster information has to travel even faster". Read More

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Forecasting COVID-19 daily cases using phone call data.

Appl Soft Comput 2021 Mar 25;100:106932. Epub 2020 Nov 25.

Cardiff School of Computer Science and Informatics, Queen's Buildings, 5 The Parade, Roath, CF24 3AA, Cardiff, UK.

The need to forecast COVID-19 related variables continues to be pressing as the epidemic unfolds. Different efforts have been made, with compartmental models in epidemiology and statistical models such as AutoRegressive Integrated Moving Average (ARIMA), Exponential Smoothing (ETS) or computing intelligence models. These efforts have proved useful in some instances by allowing decision makers to distinguish different scenarios during the emergency, but their accuracy has been disappointing, forecasts ignore uncertainties and less attention is given to local areas. Read More

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CNN-based transfer learning-BiLSTM network: A novel approach for COVID-19 infection detection.

Appl Soft Comput 2021 Jan 18;98:106912. Epub 2020 Nov 18.

Electrical and Electronics Engineering, Konya Technical University, Konya, Turkey.

Coronavirus disease 2019 (COVID-2019), which emerged in Wuhan, China in 2019 and has spread rapidly all over the world since the beginning of 2020, has infected millions of people and caused many deaths. For this pandemic, which is still in effect, mobilization has started all over the world, and various restrictions and precautions have been taken to prevent the spread of this disease. In addition, infected people must be identified in order to control the infection. Read More

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January 2021

Detecting COVID-19 patients based on fuzzy inference engine and Deep Neural Network.

Appl Soft Comput 2021 Feb 12;99:106906. Epub 2020 Nov 12.

Electronics and Communication Dept. Faculty of engineering, Mansoura University, Egypt.

COVID-19, as an infectious disease, has shocked the world and still threatens the lives of billions of people. Recently, the detection of coronavirus (COVID-19) is a critical task for the medical practitioner. Unfortunately, COVID-19 spreads so quickly between people and approaches millions of people worldwide in few months. Read More

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February 2021

AI-assisted CT imaging analysis for COVID-19 screening: Building and deploying a medical AI system.

Appl Soft Comput 2021 Jan 10;98:106897. Epub 2020 Nov 10.

State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing, China.

The sudden outbreak of novel coronavirus 2019 (COVID-19) increased the diagnostic burden of radiologists. In the time of an epidemic crisis, we hope artificial intelligence (AI) to reduce physician workload in regions with the outbreak, and improve the diagnosis accuracy for physicians before they could acquire enough experience with the new disease. In this paper, we present our experience in building and deploying an AI system that automatically analyzes CT images and provides the probability of infection to rapidly detect COVID-19 pneumonia. Read More

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January 2021

The ensemble deep learning model for novel COVID-19 on CT images.

Appl Soft Comput 2021 Jan 6;98:106885. Epub 2020 Nov 6.

School of Computer Science and Engineering, North minzu University, Yinchuan 750021, China.

The rapid detection of the novel coronavirus disease, COVID-19, has a positive effect on preventing propagation and enhancing therapeutic outcomes. This article focuses on the rapid detection of COVID-19. We propose an ensemble deep learning model for novel COVID-19 detection from CT images. Read More

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January 2021

InstaCovNet-19: A deep learning classification model for the detection of COVID-19 patients using Chest X-ray.

Appl Soft Comput 2021 Feb 29;99:106859. Epub 2020 Oct 29.

Department of Computer Science, Delhi Technological University, New Delhi, India.

Recently, the whole world became infected by the newly discovered coronavirus (COVID-19). SARS-CoV-2, or widely known as COVID-19, has proved to be a hazardous virus severely affecting the health of people. It causes respiratory illness, especially in people who already suffer from other diseases. Read More

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February 2021

Fuzzy Electromagnetism Optimization (FEMO) and its application in biomedical image segmentation.

Appl Soft Comput 2020 Dec 16;97:106800. Epub 2020 Oct 16.

Department of Computer Science & Engineering, University of Kalyani, India.

In this work, a new unsupervised classification approach is proposed for the biomedical image segmentation. The proposed method will be known as Fuzzy Electromagnetism Optimization (FEMO). As the name suggests, the proposed approach is based on the electromagnetism-like optimization (EMO) method. Read More

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December 2020