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Metaheuristic-based Deep COVID-19 Screening Model from Chest X-Ray Images

Manjit Kaur, Vijay Kumar, Vaishali Yadav, Dilbag Singh, Naresh Kumar, Nripendra Narayan Das
2021 Journal of Healthcare Engineering  
To overcome these issues, in this paper, a metaheuristic-based deep COVID-19 screening model is proposed for X-ray images.  ...  Therefore, many researchers have designed a deep learning model for the early diagnosis of COVID-19-infected patients.  ...  Literature Review In the last few months, several deep learning techniques have been rigorously used for the classification of chest X-rays for COVID-19 diagnosis.  ... 
doi:10.1155/2021/8829829 pmid:33763196 pmcid:PMC7946481 fatcat:7q54tfs5qfhv5gz54tnwcwljvy

Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoost [article]

Hamid Nasiri, Sharif Hasani
2021 arXiv   pre-print
performance in detection of COVID-19 cases from X-ray images.  ...  In the proposed method, DenseNet169 deep neural network was used to extract the features of X-ray images taken from the patients' chest and the extracted features were then given as input to the Extreme  ...  [31] proposed an enhanced Inception-ResNetV2 deep learning model for detection of COVID-19 cases from chest X-ray images.  ... 
arXiv:2109.02428v1 fatcat:rkswhdc46jctdjyutvu4hh376e

Automated deep transfer learning-based approach for detection of COVID-19 infection in chest X-rays

Nripendra Narayan Das, Naresh Kumar, Manjit Kaur, Vijay Kumar, Dilbag Singh
2020 IRBM  
Hence, the main objective of this paper is to develop an automated deep transfer learning-based approach for detection of COVID-19 infection in chest X-rays by using the extreme version of the Inception  ...  Besides this, X-rays has low ionizing radiations than CT scan. COVID-19 reveals some radiological signatures that can be easily detected through chest X-rays.  ...  Acknowledgements Authors would like to thank Manipal University Jaipur for their kind support.  ... 
doi:10.1016/j.irbm.2020.07.001 pmid:32837679 pmcid:PMC7333623 fatcat:ox654lwwvfayll3duzvcz4bvc4

Deep Transfer Learning based Classification Model for COVID-19 Disease

Yadunath Pathak, Prashant Kumar Shukla, Akhilesh Tiwari, Shalini Stalin, Saurabh Singh, Piyush Kumar Shukla
2020 IRBM  
Recently, many studies have shown that chest Computed Tomography (CT) images can be used for COVID-19 testing, as chest CT images show a bilateral change in COVID-19 infected patients.  ...  However, the classification of COVID-19 patients from chest CT images is not an easy task as predicting the bilateral change is defined as an ill-posed problem.  ...  Arya, Dr Prashant Singh Rana, Dr Shailendra Tiwari), whose work motivated us and shows a road map for the current research summarized in this paper.  ... 
doi:10.1016/j.irbm.2020.05.003 pmid:32837678 pmcid:PMC7238986 fatcat:szexlebuvjgq5bpp5arotmxc2q

Overview of current state of research on the application of artificial intelligence techniques for COVID-19

Vijay Kumar, Dilbag Singh, Manjit Kaur, Robertas Damaševičius
2021 PeerJ Computer Science  
drug discovery models for COVID-19 infected patients with the help of artificial intelligence (AI) based techniques such as machine learning and deep learning models.  ...  Results In this paper, various AI-based techniques are studied and evaluated by the means of applying these techniques for the prediction and diagnosis of COVID-19 disease.  ...  Wang, Lin & Wong (2020) developed a deep convolutional neural network (CNN) model (COVID-Net) for the identification of infection in chest X-ray images.  ... 
doi:10.7717/peerj-cs.564 pmid:34141890 pmcid:PMC8176528 fatcat:mhdwjhekgrgd5jzumt7blnshfy

A Novel COVID-19 Diagnosis Support System Using the Stacking Approach and Transfer Learning Technique on Chest X-Ray Images

Soufiane Hamida, Oussama El Gannour, Bouchaib Cherradi, Abdelhadi Raihani, Hicham Moujahid, Hassan Ouajji, Matteo Russo
2021 Journal of Healthcare Engineering  
The aim of this paper is to develop a rapid and accurate medical diagnosis support system to detect COVID-19 in chest X-ray images using a stacking approach combining transfer learning techniques and KNN  ...  To ensure the robustness of the proposed system for diagnosing patients with COVID-19 using X-ray images, we used a machine learning method called the stacking approach to combine the performances of the  ...  reduces the risk of not detecting COVID-19 cases from their chest X-rays.  ... 
doi:10.1155/2021/9437538 pmid:34777739 pmcid:PMC8589496 fatcat:czqsdw3knzh7fadmalwekxnplu

Deep Learning Approach for COVID-19 Detection Based on X-Ray Images

Hayat O. Alasasfeh, Taqwa Alomari, MS Ibbini
2021 2021 18th International Multi-Conference on Systems, Signals & Devices (SSD)  
This study aims to build a robust deep learning algorithm using convolutional neural networks (CNNs) that is capable to classify chest X-ray images into COVID-19, viral pneumonia, and normal cases.  ...  Findings prove that deep learning is an effective technique for early detection of COVID-19, it provides automatic detection with high reliability to help the healthcare professions and avoid the pandemic  ...  Machine learning and deep learning models have shown high sensitivity to COVID-19 infection in chest X-ray images, as the artificial intelligence tools help recognize details that cannot be distinguished  ... 
doi:10.1109/ssd52085.2021.9429383 fatcat:exb5mgpsazdsbew4ozv2ag73uu

Klasifikasi COVID-19 menggunakan Filter Gabor dan CNN dengan Hyperparameter Tuning

AGUS EKO MINARNO, MOCHAMMAD HAZMI COKRO MANDIRI, MUHAMMAD RIFAL ALFARIZY
2021 Jurnal Elkomika  
Filter.Keywords: COVID-19, CNN, Filter Gabor, Hyperparameter Tuning, COVID-19 Classification  ...  In this study, research was conducted to detect COVID-19 disease through CT-Scan imagery using Gabor Filter method and Convolutional Neural Networks (CNN) with Hyperparameter Tuning.  ...  Penelitian lasssinnya dilakukan oleh Hariyani dengan judul "Deteksi Penyakit Covid-19 Berdasarkan Citra X-Ray Menggunakan Deep Residual Network".  ... 
doi:10.26760/elkomika.v9i3.493 fatcat:bvz6k7iwz5er7cxiyxdgixxmgq

COVID‐opt‐aiNet : A clinical decision support system for COVID ‐19 detection

Summrina Kanwal, Faiza Khan, Sultan Alamri, Kia Dashtipur, Mandar Gogate
2022 International journal of imaging systems and technology (Print)  
Numerous studies have suggested the use of artificial intelligence (AI) and machine learning (ML) techniques to detect COVID-19 infection in patients through chest X-ray image analysis.  ...  Regrettably, due to the evolving nature of the COVID-19 global epidemic, the systematic collection of a large data set for deep neural network (DNN)/ML training is problematic.  ...  COVID-19 based on chest X-ray images.  ... 
doi:10.1002/ima.22695 pmid:35465215 pmcid:PMC9015255 fatcat:al5rumek2ffoznxua3vjzoebmm

Screening of COVID-19 Suspected Subjects using Multi-Crossover Genetic Algorithm based Dense Convolutional Neural Network

Dilbag Singh, Vijay Kumar, Manjit Kaur, Mohamed Yaseen Jabarulla, Heung-No Lee
2021 IEEE Access  
Deep transfer learning-based screening models on chest X-ray (CXR) are effective for countering the COVID-19 outbreak.  ...  In this paper, a dense convolutional neural network (DCov-Net) based transfer learning model is proposed for the screening of COVID-19 suspected subjects using CXR images.  ...  For this, chest X-ray (CXR) images are utilized to monitor the common symptoms found in infected patients.  ... 
doi:10.1109/access.2021.3120717 fatcat:hculq4bqefczdpzgycsvnulngm

Front Matter: Volume 12032

Ivana Išgum, Olivier Colliot
2022 Medical Imaging 2022: Image Processing  
of SPIE at the time of publication.  ...  Utilization of CIDs allows articles to be fully citable as soon as they are published online, and connects the same identifier to all online and print versions of the publication.  ...  Bayesian for degenerative deformities and osteoporotic fractures with 3D DeepLab 0LGraph interaction for automated diagnosis of thoracic disease using x-ray images0MInteractive deep learning for explainable  ... 
doi:10.1117/12.2638192 fatcat:ikfgnjefaba2tpiamxoftyi6sa

Multi-objective optimization determines when, which and how to fuse deep networks: an application to predict COVID-19 outcomes [article]

Valerio Guarrasi, Paolo Soda
2022 arXiv   pre-print
It exploits Pareto multi-objective optimization working with a performance metric and the diversity score of multiple candidate unimodal neural networks to be fused.  ...  The COVID-19 pandemic has caused millions of cases and deaths and the AI-related scientific community, after being involved with detecting COVID-19 signs in medical images, has been now directing the efforts  ...  e quantificazione della malattia da COVID-19" CUP D54I20001410002; EU project "University-Industrial Educational Centre in Advanced Biomedical and Medical Informatics (CeBMI) No. 612462-EPP-1-2019-1-SK-EPPKA2  ... 
arXiv:2204.03772v1 fatcat:4rxnqa226jdlldxgeaqhq46yb4

A Survey on Mathematical, Machine Learning and Deep Learning Models for COVID-19 Transmission and Diagnosis

Christopher Clement John, Vijayakumar Ponnusamy, Sriharipriya Krishnan Chandrasekaran, Nandakumar R
2021 IEEE Reviews in Biomedical Engineering  
In this aspect, a comprehensive review on the deep learning models for the diagnosis of the disease is also provided in this article.  ...  COVID-19 is a life threatening disease which has a enormous global impact.  ...  The overall accuracy of 86.7% is reported. Convolutional Neural Network-based auto diagnosis of COVID-19 for X-ray images is reported in [64] .  ... 
doi:10.1109/rbme.2021.3069213 pmid:33769936 pmcid:PMC8905610 fatcat:55fng2btxjd5jl6rfsdzypkj6q

Data-Driven Methods to Monitor, Model, Forecast and Control Covid-19 Pandemic: Leveraging Data Science, Epidemiology and Control Theory [article]

Teodoro Alamo, D. G. Reina, Pablo Millán
2020 arXiv   pre-print
This document analyzes the role of data-driven methodologies in Covid-19 pandemic.  ...  Each step of the roadmap is detailed through a review of consolidated theoretical results and their potential application in the Covid-19 context.  ...  Classification methods can be employed for diagnosis and detection of Covid-19 cases (see [189] for a review). For instance, to detect Covid-19 cases through X-ray images [107] , [138] , [164] .  ... 
arXiv:2006.01731v2 fatcat:nntq6zi4y5fkfays2qgadyio5q

2021 Index IEEE Transactions on Industrial Informatics Vol. 17

2021 IEEE Transactions on Industrial Informatics  
The Author Index contains the primary entry for each item, listed under the first author's name.  ...  -that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  ., +, TII May 2021 3663-3670 EDL-COVID: Ensemble Deep Learning for COVID-19 Case Detection From Chest X-Ray Images.  ... 
doi:10.1109/tii.2021.3138206 fatcat:ulsazxgmpfdmlivigjqgyl7zre
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