Convolutional capsnet: A novel artificial neural network approach to detect COVID-19 disease from X-ray images using capsule networks

Clinical characteristics of coronavirus disease 2019 in China

Guan, W.-J., Ni, Z.-Y., Hu, Y., Liang, W.-H., Ou, C.-Q., He, J.-X., Liu, L., Shan, H., Lei, C.-L., Hui, D. S. C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2002032 · Cited by 30,246

Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning

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ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases

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Dynamic Routing Between Capsules

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COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images

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Automated detection of COVID-19 cases using deep neural networks with X-ray images

Öztürk, T., Talo, M., Yildirim, E. A., Baloğlu, U. B., Yıldırım, Ö., & Acharya, U. R. (2020) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2020.103792 · Cited by 2,652

Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks

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Coronavirus Disease 2019 (COVID-19): A Perspective from China

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Automatic detection of coronavirus disease (COVID-19) using X-ray images and deep convolutional neural networks

Narin, A., Kaya, C., & Pamuk, Z. (2021) · Pattern Analysis and Applications · doi:10.1007/s10044-021-00984-y · Cited by 2,054

Critical Care Utilization for the COVID-19 Outbreak in Lombardy, Italy

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Aerial Separation and Receiver Arrangements on Identifying Lung Syndromes Using the Artificial Neural Network

Manoharan, H., Rambola, R. K., Kshirsagar, P. R., Chakrabarti, P., Alqahtani, J., Naveed, Q. N., Islam, S., & Mekuriyaw, W. D. (2022) · Computational Intelligence and Neuroscience · doi:10.1155/2022/7298903 · Cited by 21

A robust semantic lung segmentation study for CNN-based COVID-19 diagnosis

Aslan, M. F. (2022) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2022.104695 · Cited by 22

Developing an artificial neural network for detecting COVID-19 disease

Shanbehzadeh, M., Nopour, R., & Kazemi-Arpanahi, H. (2022) · Journal of Education and Health Promotion · doi:10.4103/jehp.jehp_387_21 · Cited by 19

Deep Learning Models for the Diagnosis and Screening of COVID-19: A Systematic Review

Siddiqui, S., Arifeen, M., Hopgood, A. A., Good, A., GEGOV, A. E., Hossain, E., Rahman, W., Hossain, S., Jannat, S. A., Ferdous, R. H., et al. (2022) · SN Computer Science · doi:10.1007/s42979-022-01326-3 · Cited by 18

SEL-COVIDNET: An intelligent application for the diagnosis of COVID-19 from chest X-rays and CT-scans

Smadi, A. A., Abugabah, A., Al-smadi, A. M., & Almotairi, S. (2022) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2022.101059 · Cited by 20

Application of Machine Learning and Deep Learning Techniques for COVID-19 Screening Using Radiological Imaging: A Comprehensive Review

Lasker, A., Obaidullah, S. M., Chakraborty, C., & Roy, K. (2022) · SN Computer Science · doi:10.1007/s42979-022-01464-8 · Cited by 19

Challenges, opportunities, and advances related to COVID-19 classification based on deep learning

Agnihotri, A., & Kohli, N. (2023) · Data Science and Management · doi:10.1016/j.dsm.2023.03.005 · Cited by 18

A Survey on Machine Learning in COVID-19 Diagnosis

Guo, X. L., Zhang, Y., Lu, S., & Lu, Z. (2021) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2021.017679 · Cited by 18

An efficient hardware architecture based on an ensemble of deep learning models for COVID -19 prediction

Sakthivel, R., Thaseen, I. S., Vanitha, M., Deepa, M., Angulakshmi, M., Ramaiah, M., Mahendran, A., Alnumay, W. S., & Chatterjee, P. (2022) · Sustainable Cities and Society · doi:10.1016/j.scs.2022.103713 · Cited by 18

TE-CapsNet: time efficient capsule network for automatic disease classification from medical images

Yadav, S., & Dhage, S. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-17458-4 · Cited by 17

Detection of COVID-19 in Chest X-Ray Images Using a CNN Model toward Medical Applications

Mohsen, S., Scholz, S. G., & Elkaseer, A. (2024) · Wireless Personal Communications · doi:10.1007/s11277-024-11309-7 · Cited by 18

COVID-19 Diagnosis from Chest X-ray Images Using Deep Learning Approach

Qaqos, N. N., & Kareem, O. S. (2020) · International Conference on Advanced Science and Engineering (ICOASE) · doi:10.1109/icoase51841.2020.9436614 · Cited by 18

COV-VGX: An automated COVID-19 detection system using X-ray images and transfer learning

Saha, P., Sadi, M. S., Aranya, O. F. M. R. R., Jahan, S., & Islam, F.-A. (2021) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2021.100741 · Cited by 16

Machine Learning Algorithms for Disease Diagnosis using Medical Records: A Comparative Analysis

Gupta, A., Chaithra, N., Jha, J., Sayal, A., Gupta, V., & Memoria, M. (2023) · International Conference on Intelligent Engineering and Management (ICIEM) · doi:10.1109/iciem59379.2023.10165850 · Cited by 16

Automatic plankton image classification—Can capsules and filters help cope with data set shift?

Plonus, R., Conradt, J., Harmer, A., Janßen, S., & Floeter, J. (2021) · Limnology and Oceanography Methods · doi:10.1002/lom3.10413 · Cited by 17

Automatic coronavirus disease 2019 diagnosis based on chest radiography and deep learning – Success story or dataset bias?

Dhont, J., Wolfs, C. J. A., & Verhaegen, F. (2021) · Medical Physics · doi:10.1002/mp.15419 · Cited by 16

An effective approach to address processing time and computational complexity employing modified CCT for lung disease classification

Khan, I. U., Azam, S., Montaha, S., Mahmud, A. A., Rafid, A. K. M. R. H., Hasan, M. Z., & Jonkman, M. (2022) · Intelligent Systems with Applications · doi:10.1016/j.iswa.2022.200147 · Cited by 18

COVID-19 Along with Other Chest Infection Diagnoses Using Faster R-CNN and Generative Adversarial Network

Mostafiz, R., Uddin, M. S., Uddin, K. M. M., & Rahman, M. M. (2022) · ACM Transactions on Spatial Algorithms and Systems · doi:10.1145/3520125 · Cited by 15

Deep learning for deterioration prediction of COVID-19 patients based on time-series of three vital signs

Mehrdad, S., Shamout, F. E., Wang, Y., & Atashzar, S. F. (2023) · Scientific Reports · doi:10.1038/s41598-023-37013-3 · Cited by 18

COVID-19 prognosis using limited chest X-ray images

Mondal, A. K. (2022) · Applied Soft Computing · doi:10.1016/j.asoc.2022.108867 · Cited by 15

GameEmo-CapsNet: Emotion Recognition from Single-Channel EEG Signals Using the 1D Capsule Networks

Toraman, S., & Dursun, Ö. O. (2021) · Traitement du signal · doi:10.18280/ts.380612 · Cited by 14

A hybrid convolutional neural network model to detect COVID ‐19 and pneumonia using chest X‐ray images

Gupta, H., Bansal, N., Garg, S., Mallik, H., Prabha, A., & Yadav, J. (2022) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22829 · Cited by 16

Artificial Intelligence Approaches on X-ray-oriented Images Process for Early Detection of COVID-19

Rezayi, S., Ghazisaeedi, M., Kalhori, S. R. N., & Saeedi, S. (2022) · Journal of Medical Signals & Sensors · doi:10.4103/jmss.jmss_111_21 · Cited by 14

A new COVID-19 classification approach based on Bayesian optimization SVM kernel using chest X-ray datasets

Lakshmi, M., Das, R., & Manohar, B. M. (2024) · Evolving Systems · doi:10.1007/s12530-024-09575-8 · Cited by 13

Wavelet Based CNN for Diagnosis of COVID 19 using Chest X Ray

Gunasekaran, S., Rajan, S., Moses, L., Vikram, S., Subalakshmi, M., & Shudhersini, B. (2021) · IOP Conference Series Materials Science and Engineering · doi:10.1088/1757-899x/1084/1/012015 · Cited by 13

A CNN-based scheme for COVID-19 detection with emergency services provisions using an optimal path planning

Barnawi, A., Chhikara, P., Tekchandani, R., Kumar, N., & Boulares, M. (2021) · Multimedia Systems · doi:10.1007/s00530-021-00833-2 · Cited by 13

COVID-19 Contact Tracing and Detection-Based on Blockchain Technology

Torky, M. F., Goda, E., Snåšel, V., & Hassanien, A. E. (2021) · Informatics · doi:10.3390/informatics8040072 · Cited by 13

Fitness dependent optimizer with neural networks for COVID-19 patients

Abdulkhaleq, M. T., Rashid, T. A., Hassan, B. A., Alsadoon, A., Bačanin, N., Chhabra, A., & Vimal, S. (2022) · Computer Methods and Programs in Biomedicine Update · doi:10.1016/j.cmpbup.2022.100090 · Cited by 18

Challenges of deep learning diagnosis for COVID-19 from chest imaging

Alaufi, R., Kalkatawi, M., & Abukhodair, F. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16017-1 · Cited by 13

A Survey on Capsule Networks: Evolution, Application, and Future Development

Li, J., Zhao, Q., Li, N., Ma, L., Xia, X., Zhang, X., Ding, N., & Li, N. (2021) · International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS) · doi:10.1109/hpbdis53214.2021.9658349 · Cited by 14

Predicting Lumbar Spondylolisthesis: A Hybrid Deep Learning Approach

Saravagi, D., Agrawal, S., Saravagi, M., Jain, S. K., Sharma, B., Mehbodniya, A., Chowdhury, S., & Webber, J. L. (2023) · Intelligent Automation & Soft Computing · doi:10.32604/iasc.2023.039836 · Cited by 12

A deep ensemble learning framework for COVID-19 detection in chest X-ray images

Asif, S., Ain, Q. U., Awais, M., Amjad, K., Bilal, O., Al-Sabri, R., & Abdullah, M. (2024) · Network Modeling Analysis in Health Informatics and Bioinformatics · doi:10.1007/s13721-024-00466-1 · Cited by 12

MedCapsNet: A modified Densenet201 model integrated with capsule network for heel disease detection and classification

Taher, O., & Özacar, K. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e34420 · Cited by 12

Boosting automatic COVID-19 detection performance with self-supervised learning and batch knowledge ensembling

Li, G., Togo, R., Ogawa, T., & Haseyama, M. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.106877 · Cited by 12

Artificial Intelligence Based COVID-19 Detection and Classification Model on Chest X-ray Images

Althaqafi, T. A., ALGhamdi, A. S. A.-M., & Ragab, M. (2023) · Healthcare · doi:10.3390/healthcare11091204 · Cited by 12

Detection of COVID-19 Disease in Chest X-Ray Images with capsul networks: application with cloud computing

Aksoy, B., & SALMAN, O. K. M. (2021) · Journal of Experimental & Theoretical Artificial Intelligence · doi:10.1080/0952813x.2021.1908431 · Cited by 12

Classification of Skin Diseases with Different Deep Learning Models and Comparison of the Performances of the Models

Doğan, F., Aktaş, M., & Gürsoy, M. İ. (2024) · Türk doğa ve fen dergisi :/Türk doğa ve fen dergisi · doi:10.46810/tdfd.1502471 · Cited by 11

Diagnosis of COVID‐19 Using a Deep Learning Model in Various Radiology Domains

Alhwaiti, Y. S., Siddiqi, M. H., Alruwaili, M., Alrashdi, I., Alanazi, S., & Jamal, M. H. (2021) · Complexity · doi:10.1155/2021/1296755 · Cited by 11

HeCapsNet : An enhanced capsule network for automated heel disease diagnosis using lateral foot X‐Ray images

Taher, O., & Özacar, K. (2024) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.23084 · Cited by 11

CNN -LSTM Based Approach for Recognition of Devanagari Manuscripts

Moudgil, A., Singh, S., & Sareen, B. (2022) · International Conference on Data Analytics for Business and Industry (ICDABI) · doi:10.1109/icdabi56818.2022.10041262 · Cited by 11

Choquet integral based deep learning model for COVID-19 diagnosis using eXplainable AI for NG-IoT models

Deepanshi, D., Budhiraja, I., Garg, D., & Kumar, N. (2023) · Computer Communications · doi:10.1016/j.comcom.2023.09.032 · Cited by 11

Deep Learning in Image Analysis for COVID-19 Diagnosis: a Survey

de Sousa, O. L. V., Magalhães, D. M. V., Vieira, P. D. A., & Silva, R. (2021) · IEEE Latin America Transactions · doi:10.1109/tla.2021.9451237 · Cited by 11

Multi-center sparse learning and decision fusion for automatic COVID-19 diagnosis

Huang, Z., Lei, H., Chen, G., Li, H., Li, C., Gao, W., Chen, Y., Wang, Y., Xu, H., Ma, G., et al. (2021) · Applied Soft Computing · doi:10.1016/j.asoc.2021.108088 · Cited by 11

Predicting Progression in Adolescent Idiopathic Scoliosis at the First Visit by Integrating 2D Imaging and 1D Clinical Information

Chu, K., Kuang, X., Cheung, P. W. H., Li, S., Zhang, T. G., & Cheung, J. P. Y. (2023) · Global Spine Journal · doi:10.1177/21925682231211273 · Cited by 11

Revolutionizing Medical Diagnosis with Novel Teaching-Learning-Based Optimization

Bakhshi, M., Karkehabadi, A., & Razavian, S. B. (2024) · International Conference on Emerging Smart Computing and Informatics (ESCI) · doi:10.1109/esci59607.2024.10497216 · Cited by 12

Meta-analysis of predictions of COVID-19 disease based on CT-scan and X-ray images

Bhatt, D. P., Bhatnagar, V., & Sharma, P. (2021) · Journal of Interdisciplinary Mathematics · doi:10.1080/09720502.2021.1884385 · Cited by 10

A survey of machine learning techniques for detecting and diagnosing COVID‐19 from imaging

Panday, A., Kabir, M. A., & Chowdhury, N. K. (2021) · Quantitative Biology · doi:10.15302/j-qb-021-0274 · Cited by 13

Shifting Capsule Networks from the Cloud to the Deep Edge

Costa, M., Costa, D. C., Gomes, T., & Pinto, S. (2022) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3544562 · Cited by 12

A deep learning approach with Bayesian optimized Kernel support vector machine for Covid-19 diagnosis

Kesav, N., & Jibukumar, M. G. (2022) · Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization · doi:10.1080/21681163.2022.2099299 · Cited by 9

LWSE: a lightweight stacked ensemble model for accurate detection of multiple chest infectious diseases including COVID-19

Asif, S., Zhao, M., Tang, F., & Zhu, Y. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16432-4 · Cited by 9

From Hume to Wuhan: An Epistemological Journey on the Problem of Induction in COVID-19 Machine Learning Models and its Impact Upon Medical Research

Vega, C. (2021) · IEEE Access · doi:10.1109/access.2021.3095222 · Cited by 10

Vision Transformer-Based Federated Learning for COVID-19 Detection Using Chest X-Ray

Sahoo, P., Saha, S., Mondal, S., Chowdhury, S., & Gowda, S. P. M. (2023) · Communications in computer and information science · doi:10.1007/978-981-99-1648-1_7 · Cited by 9

Exploring the Paradox of Bone Mineral Density in Type 2 Diabetes: A Comparative Study Using Opportunistic Chest CT Texture Analysis and DXA

Kim, M.-W., Huh, J.-W., Noh, Y. M., Seo, H. E., & Lee, D.-H. (2023) · Diagnostics · doi:10.3390/diagnostics13172784 · Cited by 9

Recognizing Edge-Based Diseases of Vocal Cords by Using Convolutional Neural Networks

Tsung, C.-K., & Tso, Y.-A. (2022) · IEEE Access · doi:10.1109/access.2022.3221457 · Cited by 8

Neural network-based strategies for automatically diagnosing of COVID-19 from X-ray images utilizing different feature extraction algorithms

Prity, F. S., Nath, N., Nath, A., & Uddin, K. M. A. (2023) · Network Modeling Analysis in Health Informatics and Bioinformatics · doi:10.1007/s13721-023-00423-4 · Cited by 8

A waste classification method based on a capsule network

Huang, L., Li, M., Xu, T., & Dong, S. (2023) · Environmental Science and Pollution Research · doi:10.1007/s11356-023-27970-7 · Cited by 8

Genetic algorithm based image reconstruction applying the digital holography process with the Discrete Orthonormal Stockwell Transform technique for diagnosis of COVID-19

Kaya, G. U., & Onur, T. Ö. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.105934 · Cited by 8

DPDH-CapNet: A Novel Lightweight Capsule Network with Non-routing for COVID-19 Diagnosis Using X-ray Images

Yuan, J., Wu, F., Li, Y., Li, J., Huang, G., & Huang, Q. (2023) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-023-00791-3 · Cited by 8

TSRNet: Diagnosis of COVID-19 based on self-supervised learning and hybrid ensemble model

Sun, J., Pi, P., Tang, C., Wang‎, S., & Zhang, Y. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.105531 · Cited by 8

Deep Learning-Based COVID-19 Detection from Chest X-ray Images: A Comparative Study

Cao, D. M., Amin, M. S., Islam, M. T., Ahmad, S. U., Haque, M. S., Sayed, M. A., Rahman, M. M., & Koli, T. (2023) · Journal of Computer Science and Technology Studies · doi:10.32996/jcsts.2023.5.4.13 · Cited by 7

THE ROLE OF D-SUMMABLE INFORMATION DIMENSION IN DIFFERENTIATING COVID-19 DISEASE

Ramírez-Arellano, A., Ortiz-Vilchis, P., & Reyes, J. B. (2021) · Fractals · doi:10.1142/s0218348x21502558 · Cited by 7

Exploiting probability density function of deep convolutional autoencoders’ latent space for reliable COVID-19 detection on CT scans

Ahrabi, S. S., Piazzo, L., Momenzadeh, A., Scarpiniti, M., & Baccarelli, E. (2022) · The Journal of Supercomputing · doi:10.1007/s11227-022-04349-y · Cited by 7

How much BiGAN and CycleGAN-learned hidden features are effective for COVID-19 detection from CT images? A comparative study

Ahrabi, S. S., Momenzadeh, A., Baccarelli, E., Scarpiniti, M., & Piazzo, L. (2022) · The Journal of Supercomputing · doi:10.1007/s11227-022-04775-y · Cited by 7

Power Line Scene Recognition Based on Convolutional Capsule Network with Image Enhancement

Zou, K., Zhao, S., & Jiang, Z. (2022) · Electronics · doi:10.3390/electronics11182834 · Cited by 7

Liver CT Image Recognition Method Based on Capsule Network

Wang, Q., Chen, A., & Xue, Y. (2023) · Information · doi:10.3390/info14030183 · Cited by 7

Machine Learning Applied to COVID-19: A Review of the Initial Pandemic Period

Mano, L. Y., Torres, A. M., Morales, A. G., Cruz, C. C. P., Cardoso, F. H., Alves, S. H., de Faria, C. O., Lanzillotti, R. S., Cerceau, R., da Costa, R. M. E. M., et al. (2023) · International Journal of Computational Intelligence Systems · doi:10.1007/s44196-023-00236-3 · Cited by 10

Res-MGCA-SE: a lightweight convolutional neural network based on vision transformer for medical image classification

Soleimani-Fard, S., & Ko, S. (2024) · Neural Computing and Applications · doi:10.1007/s00521-024-10053-0 · Cited by 7

Artificial Intelligence in Skin Cancer: Diagnosis and Therapy

Das, T., Kumar, V., Prakash, A., & Lynn, A. M. (2021) · Springer eBooks · doi:10.1007/978-981-16-0364-8_9 · Cited by 7

Indirect supervision applied to COVID-19 and pneumonia classification

Данилов, В., Proutski, A., Karpovsky, A., Kirpich, A., Litmanovich, D. E., Nefaridze, D., Talalov, O., Semyonov, S., Koniukhovskii, V., Shvartc, V., et al. (2021) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2021.100835 · Cited by 7

DSENetk: An Efficient Deep Stacking Ensemble Approach for COVID-19 Induced Pneumonia Prediction Using Radiograph Images

Chaurasia, S., Gupta‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, A. K., Tiwari, P. P., Smirti, A., & Jangid, M. (2025) · SN Computer Science · doi:10.1007/s42979-024-03603-9 · Cited by 6

Gray level co-occurrence matrix and Schmitt neural network for Covid-19 diagnosis

Pi, P. (2021) · ICST Transactions on e-Education and e-Learning · doi:10.4108/eai.11-8-2021.170668 · Cited by 6

COVID-19 Detection from Spectral Features on the DiCOVA Dataset

Ritwik, K. V. S., Kalluri, S. B., & Vijayasenan, D. (2021) · Interspeech (USB) · doi:10.21437/interspeech.2021-1031 · Cited by 6

COVID-19 Diagnosis from Medical Images Using Transfer Learning

Alshehri, E., Kalkatawi, M., Abukhodair, F., Khashoggi, K. G., & Alotaibi, R. (2022) · Saudi Journal of Health Systems Research · doi:10.1159/000521658 · Cited by 6

Covid-19 detection on x-ray images using a deep learning architecture

Akgül, İ., Kaya, V., Ünver, E., Karavaş, E., Baran, A., & Tuncer, S. (2022) · Journal of Engineering Research · doi:10.36909/jer.13901 · Cited by 6

Lung Lobe Segmentation and Feature Extraction-Based Hierarchical Attention Network for COVID-19 Prediction from Chest X-Ray Images

Magneta, S. C., Sundar, C., & Thanabal, M. S. (2022) · The Computer Journal · doi:10.1093/comjnl/bxac136 · Cited by 6

CoroTrans-CL: A Novel Transformer-Based Continual Deep Learning Model for Image Recognition of Coronavirus Infections

Wang, B., Zhang, D., & Tian, Z. (2023) · Electronics · doi:10.3390/electronics12040866 · Cited by 6

ML-CapsNet meets VB-DI-D: A novel distortion-tolerant baseline for perturbed object recognition

Lin, Z., Zheng, Z., Jia, J., Gao, W., & Huang, F. (2023) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2023.105937 · Cited by 6

IRCM‐Caps: An X‐ray image detection method for COVID‐19

Qiu, S., Ma, J., & Ma, Z. (2023) · The Clinical Respiratory Journal · doi:10.1111/crj.13599 · Cited by 5

COVID-19 Diagnosis in Computerized Tomography (CT) and X-ray Scans Using Capsule Neural Network

Akinyelu, A. A., & Bah, B. (2023) · Diagnostics · doi:10.3390/diagnostics13081484 · Cited by 6

Spectroscopic characterisation of feedstock for copper smelters by machine-learning

Bernicky, A. R., Davis, B., Barnes, J. A., & Loock, H. (2023) · Canadian Metallurgical Quarterly · doi:10.1080/00084433.2023.2215013 · Cited by 6

Emergence of Capsule Network for Automatic Medical Disease Classification

Yadav, S., & Dhage, S. (2022) · Sardar Patel International Conference on Industry 4.0 - Nascent Technologies and Sustainability for 'Make in India' Initiative · doi:10.1109/spicon56577.2022.10180503 · Cited by 6

Hybridizing Artificial Neural Networks Through Feature Selection Based Supervised Weight Initialization and Traditional Machine Learning Algorithms for Improved Colon Cancer Prediction

Nadeem, M. S. A., Waseem, M. H., Aziz, W., Habib, U., Masood, A., & Khan, M. A. (2024) · IEEE Access · doi:10.1109/access.2024.3422317 · Cited by 10

Prediction of viral-host interactions of COVID-19 by computational methods

Alakuş, T. B., & Türkoğlu, İ. (2022) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/j.chemolab.2022.104622 · Cited by 5

Deep-COVID: Detection and Analysis of COVID-19 Outcomes Using Deep Learning

Khalil, M. I., Rehman, S. U., Alhajlah, M., Mahmood, A., Karamat, T., Haneef, M., & Alhajlah, A. (2022) · Electronics · doi:10.3390/electronics11223836 · Cited by 5

COVID19-ResCapsNet: A Novel Residual Capsule Network for COVID-19 Detection from Chest X-Ray Scans Images

Li, Z., Xing, Q., Zhao, J., Yu, M., Zhang, K., Feng, G., Qu, F., Li, Y., He, W., Shi, W., et al. (2023) · IEEE Access · doi:10.1109/access.2023.3279402 · Cited by 5

A Deep Learning Model Based on Capsule Networks for COVID Diagnostics through X-ray Images

Rangel, G., Cuevas-Tello, J. C., Rivera, M., & Renteria, O. (2023) · Diagnostics · doi:10.3390/diagnostics13172858 · Cited by 5

An Integrative Method for COVID-19 Patients’ Classification from Chest X-ray Using Deep Learning Network with Image Visibility Graph as Feature Extractor

Pal, M., Tiwari, Y., Reddy, T. V., Aditya, P. S. R., & Panigrahi, P. K. (2023) · Communications in computer and information science · doi:10.1007/978-3-031-48876-4_21 · Cited by 5

Optimising Chest X-Rays for Image Analysis by Identifying and Removing Confounding Factors

Aslani, S., Lilaonitkul, W., Gnanananthan, V., Raj, D., Rangelov, B., Young, A. L., Hu, Y., Taylor, P. M., Alexander, D. C., Collaborative, N., et al. (2023) · Lecture notes in electrical engineering · doi:10.1007/978-981-16-6775-6_20 · Cited by 8

Multi-Lane Capsule Network Architecture for Detection of COVID-19

Sridhar, S., & Sanagavarapu, S. (2021) · International Conference on Intelligent Engineering and Management (ICIEM) · doi:10.1109/iciem51511.2021.9445363 · Cited by 5

X-Ray Covid-19 Detection Based on Scatter Wavelet Transform and Dense Deep Neural Network

Al-Itbi, A. S., Alwahhab, A. B. A., & Sahan, A. M. (2021) · Computer Systems Science and Engineering · doi:10.32604/csse.2022.021980 · Cited by 5

A NOVEL COMPARATIVE STUDY FOR AUTOMATIC THREE-CLASS AND FOUR-CLASS COVID-19 CLASSIFICATION ON X-RAY IMAGES USING DEEP LEARNING

Yaşar, H., & Ceylan, M. (2022) · Malaysian Journal of Computer Science · doi:10.22452/mjcs.vol35no4.5 · Cited by 5

An optimized KELM approach for the diagnosis of COVID-19 from 2D-SSA reconstructed CXR Images

Mohanty, F., & Dora, C. (2021) · Optik · doi:10.1016/j.ijleo.2021.167572 · Cited by 5

Ensemble Learning Models Coupled with Urban Mobility Information Applied to Predict COVID-19 Incidence Cases

Ribeiro, M. H. D. M., da Silva, R. G., Larcher, J. H. K., Mariani, V. C., & Coelho, L. D. S. (2021) · Studies in systems, decision and control · doi:10.1007/978-3-030-72834-2_24 · Cited by 5

Efficiency of Artificial Intelligence in Detecting COVID-19 Pneumonia and Other Pneumonia Causes by Quantum Fourier Transform MethodPreprint

Acar, E., Öztoprak, B., Reşorlu, M., Daş, M., Yılmaz, İ., & Öztoprak, İ. (2021) · medRxiv · doi:10.1101/2020.12.29.20248900 · Cited by 7

Neural Networks for Infectious Diseases Detection: Prospects and ChallengesPreprint

Javaid, S., & Saeed, N. (2021) · doi:10.36227/techrxiv.16682206 · Cited by 9

Deep learning based capsule networks for breast cancer classification using ultrasound images

Afrifa, S., Vijayakumar, V., Zhang, T., Appiahene, P., Gyamfi, D., Gyening, R.-M. O. M., Mensah, J., & Berchie, S. O. (2024) · Current Cancer Reports · doi:10.25082/ccr.2024.01.002 · Cited by 4

Capsule Network Versus Convolutional Neural Network in Image Classification

Juralewicz, E., & Markowska–Kaczmar, U. (2021) · Lecture notes in computer science · doi:10.1007/978-3-030-77977-1_2 · Cited by 4

Study of Metadata Impact on COVID-19 Detection using Convolutional Neural Networks

Sedaghati, N., & Abbasi, B. (2022) · IEEE International Conference on Information Reuse and Integration (IRI) · doi:10.1109/iri54793.2022.00070 · Cited by 4

(XAI-AGUWEM) Explainable Artificial Intelligence-based Attention Guided Uncertainty Weighting Ensemble Model for the Classification of COVID-19 and Pneumonia in X-ray Medical Images

Agnihotri, A., & Kohli, N. (2025) · Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) · doi:10.2174/0123520965334135241115064754 · Cited by 4

Random Satisfiability Logic-Driven Approach in the Hopfield Neural Networks with Application to COVID-19 Datasets

Abubakar, H. (2025) · International Journal of Applied and Computational Mathematics · doi:10.1007/s40819-025-01941-7 · Cited by 4

COVID-WideNet—A capsule network for COVID-19 detection

Gupta, P. K., Siddiqui, M. K., Huang, X., Morales-Menéndez, R., Panwar, H., Terashima‐Marín, H., & Wajid, M. S. (2022) · Applied Soft Computing · doi:10.1016/j.asoc.2022.108780 · Cited by 40

Conv-CapsNet: capsule based network for COVID-19 detection through X-Ray scans

Sharma, P., Arya, R., Verma, R., & Verma, B. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-14353-w · Cited by 23

Initial Stage Identification of COVID-19 Using Capsule Networks

Ganesan, S., Anand, R., Sowmya, V., & Soman, K. P. (2022) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-031-20541-5_9

Detection of COVID-19 disease from X-ray images using capsule-based network

Ashtiani Haghighi, D. (2022) · UVic’s Research and Learning Repository (University of Victoria)

A Novel Model for Detection and Classification Coronavirus (COVID-19) Based on Chest X-Ray Images Using CNN-CapsNet

Yousra, D., Abdelhakim, B. A., & Ahmed, M. B. (2021) · Lecture notes in networks and systems · doi:10.1007/978-3-030-78901-5_17 · Cited by 6