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Symptoms-Based Fuzzy-Logic Approach for COVID-19 Diagnosis

Maad Shatnawi, Anas Shatnawi, Zakarea AlShara, Ghaith Husari
2021 International Journal of Advanced Computer Science and Applications  
The system infers the likelihood level of COVID-19 infection based on the symptoms that appear on the patient.  ...  In this paper, we introduce an intelligent fuzzy inference system for the primary diagnosis of COVID-19.  ...  (CT) scan and X-ray imaging.  ... 
doi:10.14569/ijacsa.2021.0120457 fatcat:ycoqdpblgbcmjbxx3ilktdnj74

Computational Intelligence Techniques for Combating COVID-19: A Survey

Vincent S. Tseng, Josh Jia-Ching Ying, Stephen T.C. Wong, Diane J. Cook, Jiming Liu
2020 IEEE Computational Intelligence Magazine  
computational intelligence to combat COVID-19.  ...  Such inconvenience has hindered the development of effective computational intelligence technologies for fighting COVID-19.  ...  [48] developed an ensemble model to identify COVID-19 infections, which can allow early identification of COVID-19 patients at an early stage based on the initial chest CT scans and related clinical  ... 
doi:10.1109/mci.2020.3019873 fatcat:7iji6n35o5egjdonbxoqwjkmia

Accelerated Diagnosis of Novel Coronavirus (COVID-19)—Computer Vision with Convolutional Neural Networks (CNNs)

Arfan Ghani, Akinyemi Aina, Chan Hwang See, Hongnian Yu, Simeon Keates
2022 Electronics  
This study demonstrated an integrated method to accelerate the process of classifying CT scan images.  ...  This paper reviewed the current CNN-based approaches and investigated a custom-designed CNN method to detect COVID-19 symptoms from CT (Computed Tomography) chest scan images.  ...  Acknowledgments: We acknowledge the hardware/software support provided by the American University of Ras al Khaimah, UAE.  ... 
doi:10.3390/electronics11071148 fatcat:j5gypot2f5akdhrrpdztmo5pyy

An Unsupervised Fuzzy Clustering Approach for Early Screening of COVID-19 from Radiological Images

Weiping Ding, Shouvik Chakraborty, Kalyani Mali, Sankhadeep Chatterjee, Janmenjoy Nayak, Asit Kumar Das, Soumen Banerjee
2021 IEEE transactions on fuzzy systems  
A global pandemic scenario is witnessed worldwide owing to the menace of the rapid outbreak of the deadly COVID-19 virus.  ...  Although the proposed approach performs well but should not be considered as an alternative to gold standard detection tests of COVID-19.  ...  On the other hand, chest CT scans or X-Rays show some vital patterns that can be a hint of COVID-19 infection.  ... 
doi:10.1109/tfuzz.2021.3097806 fatcat:mgv47veizfgefbwf3vj6pme3ku

Analysis of Artificial Intelligence Technologies Used In The Covid-19 Outbreak Process

2020 International Journal of Applied Mathematics Electronics and Computers  
Then, the applications developed using artificial intelligence technologies during the coronavirus (Covid-19) epidemic process were evaluated and the adequacy of the applications developed by analysing  ...  Accordingly, the use of artificial intelligence technologies in different areas, especially in medicine, played an important role in combating the epidemic during the coronavirus (Covid-19) epidemic process  ...  Author's Note Abstract version of this paper was presented at 9th International Conference on Advanced Technologies (ICAT'20), 10-12 August 2020, Istanbul, Turkey with the title of "Analysis of Artificial  ... 
doi:10.18100/ijamec.800910 fatcat:hpmdvqutwjhknig7bbb7zhtove

Fuzzy rank-based fusion of CNN models using Gompertz function for screening COVID-19 CT-scans

Rohit Kundu, Hritam Basak, Pawan Kumar Singh, Ali Ahmadian, Massimiliano Ferrara, Ram Sarkar
2021 Scientific Reports  
To this end, in this paper, we propose an automated COVID-19 detection system that uses CT-scan images of the lungs for classifying the same into COVID and Non-COVID cases.  ...  The framework has been evaluated on two publicly available chest CT scan datasets achieving state-of-the-art performance, justifying the reliability of the model.  ...  Acknowledgements The authors would like to thank the Centre for Microprocessor Applications for Training, Education and Research (CMATER) research laboratory of the Computer Science and Engineering Department  ... 
doi:10.1038/s41598-021-93658-y pmid:34238992 fatcat:63akikrta5cmpcr7w3xugmtmv4

Author Index

2021 2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)  
Using Structural Equation Modeling 68 Similarity Normalized Euclidean Distance on KNN Method to Classify Image of Skin Cancer 532 COVID-19 Detection Model on Chest CT Scan and X-ray Images Using VGG16  ...  KNN Method to Classify Image of Skin Cancer COVID-19 Detection Model on Chest CT Scan and X-ray Images Using VGG16 Convolutional Neural Network Input Feature Selection in ECG Signal Data Modelling using  ... 
doi:10.1109/isriti54043.2021.9702846 fatcat:ferqbimf5rfztc246rtvmppqxq

Automated Diagnosis of COVID-19 using Deep Features and Parameter Free BAT Optimization

Taranjit Kaur, Tapan K. Gandhi, Bijaya K. Panigrahi
2021 IEEE Journal of Translational Engineering in Health and Medicine  
Extensive research has been reported using deep learning models to diagnose the severity of COVID-19 from CT images.  ...  However, the existing problems can be improved by employing computational intelligent techniques on radiological images like CT-Scans (Computed Tomography) of lungs.  ...  based on the integration of MobineNetv2 architecture with Parameter Free BAT(PF-BAT) optimized Fuzzy KNN(FKNN) classifier for the automated classification of COVID-19 CT scans.  ... 
doi:10.1109/jtehm.2021.3077142 pmid:34235005 pmcid:PMC8248768 fatcat:5kkmc3nzyrhr5mlmosqgxjk6ry

COVID-X: Novel Health-Fog Framework Based on Neutrosophic Classifier for Confrontation Covid-19

Ibrahim Yasser, Abeer Twakol, A. A. Abd El-Khalek, Ahmed Samrah, A. A. Salama
2020 Zenodo  
based on target application.  ...  There are some proposed applications based on the proposed COVID-X framework such as smart mask, smart medical suit, safe spacer, and Medical Mobile Learning (MML) will be presented.  ...  [19] proposed a machine learning approach for COVID-19 classification from CT images. Kassani et al.  ... 
doi:10.5281/zenodo.3951625 fatcat:bsjm5rd3nvcmdmhzzwakidewq4

Method of Intelligent Diagnosis of Covid-19 Based on a Neural Network of Generalized Bell-Shaped Functions and Fuzzy Logic

Eugene Fedorov, Jihed Draouil, Kostiantyn Rudakov, Hamza Alrababah, Tetyana Utkina, Ihor Zubko
2021 International Workshop on Informatics & Data-Driven Medicine  
The paper proposes a method for intelligent diagnosis of COVID-19 based on a neural network of generalized bell-shaped functions and fuzzy logic.  ...  The author's method of intelligent diagnostics can be used in COVID-19 in various intelligent systems of medical diagnostics.  ...  The proposed method for intelligent diagnosis of COVID-19 is based on fuzzy logic and artificial neural networks for analysis CXR image; providing a representation of knowledge about the diagnosis of COVID  ... 
dblp:conf/iddm/FedorovDRAUZ21 fatcat:qfcnsc5xz5gcleppvheq5fglri

Fuzzy Unique Image Transformation: Defense Against Adversarial Attacks On Deep COVID-19 Models [article]

Achyut Mani Tripathi, Ashish Mishra
2020 arXiv   pre-print
Early identification of COVID-19 using a deep model trained on Chest X-Ray and CT images has gained considerable attention from researchers to speed up the process of identification of active COVID-19  ...  CT image Datasets.  ...  Results on CT Image Dataset The proposed model is also evaluated on second available CT Scan Image Dataset [50] for the diagnosis of COVID-19.  ... 
arXiv:2009.04004v1 fatcat:i27hkvzqxfhdpnqgavdczv6kwe

Artificial Intelligence in the Battle against Coronavirus (COVID-19): A Survey and Future Research Directions

Thanh Thi Nguyen
This paper presents a survey of AI methods being used in various applications in the fight against the COVID-19 outbreak and outlines the crucial roles of AI research in this unprecedented battle.  ...  against COVID-19.  ...  Distinct manifestations of CT images of COVID-19 found in previous [8] for COVID-19 detection using CT images.  ... 
doi:10.6084/m9.figshare.12127020.v6 fatcat:uhlfvss2cvcnphivhgqns7nl7q

A Few-Shot U-Net Deep Learning Model for COVID-19 Infected Area Segmentation in CT Images

Athanasios Voulodimos, Eftychios Protopapadakis, Iason Katsamenis, Anastasios Doulamis, Nikolaos Doulamis
2021 Sensors  
Recent studies indicate that detecting radiographic patterns on CT chest scans can yield high sensitivity and specificity for COVID-19 identification.  ...  In this paper, we scrutinize the effectiveness of deep learning models for semantic segmentation of pneumonia-infected area segmentation in CT images for the detection of COVID-19.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s21062215 pmid:33810066 fatcat:j6pi7g33tbcbxiylgra5gsv2ja

Artificial Intelligence: A Survey on Evolution and Future Trends

Maad M. Mijwil, Rana A. Abttan
2021 Asian Journal of Applied Sciences  
In addition, there is a review of Expert Systems, Artificial Neural Networks, Fuzzy Logic, and AI applications in the medical field and power systems, especially in investigating lung images of people  ...  with COVID-19.  ...  systems Figure 8 : 8 (a) X-rays and CT scan-images of infected persons with COVID-19, (b) Caricature image by Schmidhuber.  ... 
doi:10.24203/ajas.v9i2.6589 fatcat:h4nxkbbpfrhspa6ol5pgb3tney

Artificial Intelligence in the Battle against Coronavirus (COVID-19): A Survey and Future Research Directions [article]

Thanh Thi Nguyen, Quoc Viet Hung Nguyen, Dung Tien Nguyen, Samuel Yang, Peter W. Eklund, Thien Huynh-The, Thanh Tam Nguyen, Quoc-Viet Pham, Imran Razzak, Edbert B. Hsu
2022 arXiv   pre-print
This paper presents a survey of AI methods being used in various applications in the fight against the COVID-19 outbreak and outlines the crucial role of AI research in this unprecedented battle.  ...  fight against COVID-19.  ...  and computed tomography (CT) scans.  ... 
arXiv:2008.07343v4 fatcat:k4mvvml2hbaxdjyvaw3fbqlon4
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