COVID-19 image classification using deep learning: Advances, challenges and opportunities

Deep Residual Learning for Image Recognition

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Densely Connected Convolutional Networks

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Going deeper with convolutions

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Fully convolutional networks for semantic segmentation

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A novel coronavirus from patients with pneumonia in China, 2019

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Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization

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Deep learning techniques for detection and prediction of pandemic diseases: a systematic literature review

Ajagbe, S. A., & Adigun, M. O. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-15805-z · Cited by 141

Deep Learning for Pneumonia Detection in Chest X-ray Images: A Comprehensive Survey

Siddiqi, R., & Javaid, S. (2024) · Journal of Imaging · doi:10.3390/jimaging10080176 · Cited by 145

Automated detection and forecasting of COVID-19 using deep learning techniques: A review

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A methodical exploration of imaging modalities from dataset to detection through machine learning paradigms in prominent lung disease diagnosis: a review

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A Holistic Approach to Identify and Classify COVID-19 from Chest Radiographs, ECG, and CT-Scan Images Using ShuffleNet Convolutional Neural Network

Ullah, N., Khan, J. A., El–Sappagh, S., El-Rashidy, N. M., & Khan, M. S. (2023) · Diagnostics · doi:10.3390/diagnostics13010162 · Cited by 73

Application of Semi-Supervised Learning in Image Classification: Research on Fusion of Labeled and Unlabeled Data

Li, S., Peng, K., Ma, M., Yang, H., Huang, S., & Yang, Z. (2024) · IEEE Access · doi:10.1109/access.2024.3367772 · Cited by 72

Lightweight deep CNN-based models for early detection of COVID-19 patients from chest X-ray images

Hussein, H. I., Mohammed, A. O., Hassan, M. M., & Mstafa, R. J. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.119900 · Cited by 78

A review on lung disease recognition by acoustic signal analysis with deep learning networks

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A Soft-Voting Ensemble Classifier for Detecting Patients Affected by COVID-19

Manconi, A., Giuliano Armano, B., Gnocchi, M., & Milanesi, L. (2022) · Applied Sciences · doi:10.3390/app12157554 · Cited by 54

ECG-iCOVIDNet: Interpretable AI model to identify changes in the ECG signals of post-COVID subjects

Agrawal, A., Chauhan, A., Shetty, M. K., Girish, M. P., Gupta, M. D., & Gupta, A. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.105540 · Cited by 40

A deep CNN approach to detect and classify local fruits through a web interface

Rahman, M. M., Basar, M. A., Shinti, T. S., Khan, M. S. I., Babu, H. M. H., & Uddin, K. M. M. (2023) · Smart Agricultural Technology · doi:10.1016/j.atech.2023.100321 · Cited by 38

A review of deep learning approaches in clinical and healthcare systems based on medical image analysis

Helaly, H. A., Badawy, M., & Haikal, A. Y. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16605-1 · Cited by 34

An Artificial Intelligence-as-a-Service Architecture for deep learning model embodiment on low-cost devices: A case study of COVID-19 diagnosis

Moreira, L. F. R., Moreira, R., Travençolo, B. A. N., & Backes, A. R. (2023) · Applied Soft Computing · doi:10.1016/j.asoc.2023.110014 · Cited by 30

A novel lightweight deep learning model based on SqueezeNet architecture for viral lung disease classification in X-ray and CT images

Agnihotri, A., & Kohli, N. (2024) · International Journal of Computational and Experimental Science and Engineering · doi:10.22399/ijcesen.425 · Cited by 32

Automated diagnosis of COVID stages using texture‐based Gabor features in variational mode decomposition from CT images

Patel, R. K., & Kashyap, M. (2023) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22865 · Cited by 27

An Ensemble Machine Learning and Data Mining Approach to Enhance Stroke Prediction

Wijaya, R., Saeed, F., Samimi, P., Albarrak, A. M., & Qasem, S. N. (2024) · Bioengineering · doi:10.3390/bioengineering11070672 · Cited by 23

Deep Learning in COVID-19 Diagnosis, Prognosis and Treatment Selection

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High-Performance Convolutional Neural Network Model to Identify COVID-19 in Medical Images

Sunarjo, M. S., Gan, H., & Setiadi, D. R. I. M. (2023) · Journal of Computing Theories and Applications · doi:10.33633/jcta.v1i1.8936 · Cited by 23

Review of neuromorphic computing based on NAND flash memory

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RVCNet: A hybrid deep neural network framework for the diagnosis of lung diseases

Alam, F. B., Podder, P., & Mondal, M. R. H. (2023) · PLoS ONE · doi:10.1371/journal.pone.0293125 · Cited by 22

CNN or RNN: Review and Experimental Comparison on Image Classification

Junliang, C. (2022) · IEEE International Conference on Computer and Communications (ICCC) · doi:10.1109/iccc56324.2022.10065984 · Cited by 20

MERGE: A model for multi-input biomedical federated learning

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COVID-19 diagnosis via chest X-ray image classification based on multiscale class residual attention

Liu, S.-W., Cai, T., Tang, X., Zhang, Y., & Wang, C. (2022) · Comput. Biol. Medicine · doi:10.1016/j.compbiomed.2022.106065 · Cited by 15

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

Minimizing Liability of the COVID-19 Pandemic on Construction Contracts—A Structural Equation Model for Risk Mitigation of Force Majeure Impacts

Chadee, A. A., Gallage, S., Martin, H. G., Rathnayake, U., Ray, I., Kumar, B., & Sihag, P. (2022) · Buildings · doi:10.3390/buildings13010070 · Cited by 17

GFN: A Garbage Classification Fusion Network Incorporating Multiple Attention Mechanisms

Wang, Z., Zhou, W., & Li, Y. (2024) · Electronics · doi:10.3390/electronics14010075 · Cited by 17

Transfer learning with CNNs for efficient prostate cancer and BPH detection in transrectal ultrasound images

Huang, T.-L., Lu, N., Huang, Y.-H., Twan, W., Yeh, L.-R., Liu, K., & Chen, T. (2023) · Scientific Reports · doi:10.1038/s41598-023-49159-1 · Cited by 15

PP-CNN: probabilistic pooling CNN for enhanced image classification

Mishra, N. K., Singh, P., Gupta, A., & Joshi, S. D. (2024) · Neural Computing and Applications · doi:10.1007/s00521-024-10862-3 · Cited by 15

Attention induced multi-head convolutional neural network organization with MobileNetv1 transfer learning and COVID-19 diagnosis using jellyfish search optimization process on chest X-ray images

Ramkumar, M., Gowtham, M. S., Jamaesha, S. S., & Vigenesh, M. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.106133 · Cited by 14

Omni-dimensional dynamic convolution feature coordinate attention network for pneumonia classification

Li, Y., Xin, Y., Li, X., Zhang, Y., Liu, C., Cao, Z., Du, S., & Wang, L. (2024) · Visual Computing for Industry Biomedicine and Art · doi:10.1186/s42492-024-00168-5 · Cited by 14

Transfer learning with convolutional neural networks for hydrological streamline delineation

Jaroenchai, N., Wang, S., Stanislawski, L. V., Shavers, E. J., Jiang, Z., Sagan, V., & Usery, E. L. (2024) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2024.106165 · Cited by 16

COV-MobNets: a mobile networks ensemble model for diagnosis of COVID-19 based on chest X-ray images

Eshraghi, M. A., Ayatollahi, A., & Shokouhi, S. B. (2023) · BMC Medical Imaging · doi:10.1186/s12880-023-01039-w · Cited by 15

COVIDX-LwNet: A Lightweight Network Ensemble Model for the Detection of COVID-19 Based on Chest X-ray Images

Wang, W., Liu, S., Xu, H., & Deng, L. (2022) · Sensors · doi:10.3390/s22218578 · Cited by 12

Enhanced deep transfer learning with multi-feature fusion for lung disease detection

Vidyasri, S., & Saravanan, S. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-17767-8 · Cited by 11

A deep transfer learning approach for COVID-19 detection and exploring a sense of belonging with Diabetes

Ahmad, I., Merla, A., Ali, F., Shah, B., AlZubi, A. A., & AlZubi, M. A. (2023) · Frontiers in Public Health · doi:10.3389/fpubh.2023.1308404 · Cited by 12

E-GCS: Detection of COVID-19 through classification by attention bottleneck residual network

Ahila, T., & Subhajini, A. C. (2022) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2022.105398 · Cited by 11

A survey of generative adversarial networks and their application in text-to-image synthesis

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DAEGAN: Generative adversarial network based on dual-domain attention-enhanced encoder-decoder for low-dose PET imaging

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Scientific pertinence of developing machine learning technologies for the triage of COVID-19 patients: A bibliometric analysis via Scopus

Ballaz, S., Pulgar-Sánchez, M., Chamorro, K., & Fernández-Moreira, E. (2023) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2023.101312 · Cited by 11

Histopathology-Based Prostate Cancer Classification Using ResNet: A Comprehensive Deep Learning Analysis

Emegano, D. I., Mustapha, M. T., Ozsahin, D. U., Özşahin, İ., & Uzun, B. (2025) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-025-01543-1 · Cited by 9

Using Artificial Intelligence for COVID-19 Detection in Blood Exams: A Comparative Analysis

Loddo, A., Meloni, G., & Pes, B. (2022) · IEEE Access · doi:10.1109/access.2022.3221750 · Cited by 9

Innovation through Artificial Intelligence in Triage Systems for Resource Optimization in Future Pandemics

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Medical imaging-based artificial intelligence in pneumonia: A narrative review

Yang, Y., Xing, W., Liu, Y., Li, Y., Ta, D., Song, Y., & Hou, D. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.129731 · Cited by 9

Enhanced deep learning framework for efficient garbage classification in smart waste management systems

Ghosh, D., & Goswami, A. (2025) · Information Sciences · doi:10.1016/j.ins.2025.122462 · Cited by 8

MinoritySalMix and adaptive semantic weight compensation for long-tailed classification

Zeng, W., & Xiao, Z.-Y. (2024) · Image and Vision Computing · doi:10.1016/j.imavis.2024.105307 · Cited by 8

CNN Ensemble Learning Method for Transfer learning: A Review

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FLEM-XAI: Federated learning based real time ensemble model with explainable AI framework for an efficient diagnosis of lung diseases

Durga, S., Daniel, E., Seetha, S., Reshma, V. K., & Sachnev, V. (2025) · Frontiers in Computer Science · doi:10.3389/fcomp.2025.1633916 · Cited by 10

Applications of AI/ML in accelerating the development of pulmonary drug delivery system

Jiang, J., Zhou, Z., Peng, T., Huang, Z., Pan, X., & Wu, C. (2025) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2025.11.028 · Cited by 7

Classification of COVID-19 patients from HRCT score prediction in CT images using transfer learning approach

Tembhurne, J. V. (2024) · Journal of Electrical Systems and Information Technology · doi:10.1186/s43067-023-00129-7 · Cited by 7

COVID-19 lateral flow test image classification using deep CNN and StyleGAN2

Venugopal, V. P., Saheer, L. B., & Oghaz, M. M. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2023.1235204 · Cited by 8

A high-accuracy lightweight network model for X-ray image diagnosis: A case study of COVID detection

Wang, S., Ren, J., & Guo, X. (2024) · PLoS ONE · doi:10.1371/journal.pone.0303049 · Cited by 9

A Light Deep Learning Algorithm for CT Diagnosis of COVID-19 Pneumonia

Furtado, A. N., da Purificação, C. A. C., Badaró, R. J. D. S., & Nascimento, E. G. S. (2022) · Diagnostics · doi:10.3390/diagnostics12071527 · Cited by 7

An Effective Approach for Automatic COVID-19 Detection from Multiple Image Sources Using Shufflenet Convolutional Neural Network (CNN)Preprint

Ullah, N., Raza, A., Khan, J. A., & Khan, A. A. (2022) · Research Square · doi:10.21203/rs.3.rs-1668838/v1 · Cited by 7

Hybrid Deep Learning Architecture for Land Use - Land Cover Images Classification with a Comparative and Experiemental Study

Salhi, W., Tabiti, K., Honnit, B., Nabil, S. M., & Kabbaj, A. (2022) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2022.01312104 · Cited by 8

HyCoViT: Hybrid Convolution Vision Transformer With Dynamic Dropout for Enhanced Medical Chest X-Ray Classification

Almasi, O. N., Ling, N., & Li, X. (2025) · IEEE Access · doi:10.1109/access.2025.3584065 · Cited by 9

Transfer Learning Fusion and Stacked Auto-encoders for Viral Lung Disease Classification

Ketfi, M., Belahcene, M., & Bourennane, S. (2024) · New Generation Computing · doi:10.1007/s00354-024-00247-4 · Cited by 6

Chaotic Satin Bowerbird Optimizer Based Advanced AI Techniques for Detection of COVID-19 Diseases from CT Scans Images

Maheswari, V. U., Stephe, S., Aluvalu, R., Thirumalraj, A., & Mohanty, S. N. (2024) · New Generation Computing · doi:10.1007/s00354-024-00279-w · Cited by 6

Automatic COVID-19 Detection from Chest X-ray using Deep MobileNet Convolutional Neural Network

Al-Qazzaz, N. K., Aldoori, A. A., Ali, S. H. M., & Ahmad, S. A. (2024) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc53108.2024.10781897 · Cited by 6

Dataset Generator: Creating And Analyzing Customized Data

Sangidwar, S., Mane, S., Hussain, S., Lokhande, S., Deshmukh, R., & Mungale, N. (2023) · International Conference on Emerging Trends in Engineering and Technology (ICETET) · doi:10.1109/icetet-sip58143.2023.10151469 · Cited by 6

A novel IoT-based deep neural network for COVID-19 detection using a soft-attention mechanism

Fki, Z., Ammar, B., Fourati, R., Fendri, H., Daoued, E., Mnif, Z., Hussain, A., & Ayed, M. B. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-17642-6 · Cited by 8

TransfusionNet: Framework for cervical cancer detection using deep learning with multi-level fusion

Hasan, M. N., Shuvo, S. B., Ankon, M. H., Raju, S. M. T. U., & Siddique, N. H. (2025) · Results in Engineering · doi:10.1016/j.rineng.2025.107174 · Cited by 5

Multi-class nonparallel support vector machine

Sahleh, A., Salahi, M., & Eskandari, S. (2023) · Progress in Artificial Intelligence · doi:10.1007/s13748-023-00308-7 · Cited by 5

Enhancing COVID-19 diagnosis from lung CT scans using optimized quantum-inspired complex convolutional neural network with ResNeXt-50

Saranya, R., & Jaichandran, R. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.106295 · Cited by 5

Skin Disease Classification with Help of Artificial Intelligence Techniques

Agarwal, M., Kaliyar, R. K., & Mehta, V. (2024) · International Conference on Computational Intelligence and Communication Networks (CICN) · doi:10.1109/cicn63059.2024.10847516 · Cited by 5

COVID-19 CXR Classification: Applying Domain Extension Transfer Learning and Deep Learning

Park, K., Choi, Y., & Lee, H.-C. (2022) · Applied Sciences · doi:10.3390/app122110715 · Cited by 5

Artificial intelligence-powered prediction of diabetic complications: from clinical data to molecular omics

Xie, X., Wu, C., Huang, Z., Zhou, Y., Huang, J., Dao, F., Yan, D., Deng, K., Lyu, H., Ma, C., et al. (2026) · Briefings in Bioinformatics · doi:10.1093/bib/bbag083 · Cited by 4

Deep learning for detecting early gastric cancer with white-light endoscopy: a systematic review and meta-analysis

Liu, J., Li, D., Zhuo, Y., & Zhang, S. (2026) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2026.1734591 · Cited by 4

An Enhanced Framework for Overcoming Pitfalls and Enabling Model Interpretation in Pneumonia and Covid-19 Classification

Santos, M. A. D. C., & Berton, L. (2023) · IEEE Access · doi:10.1109/access.2023.3325404 · Cited by 4

The role of advanced machine learning in COVID-19 medical imaging: A technical review

Fayyaz, A. M., Abdulkadir, S. J., Hassan, S. U., Al-Selwi, S. M., Sumiea, E. H., & Talib, L. F. (2025) · Results in Engineering · doi:10.1016/j.rineng.2025.105154 · Cited by 4

Deep Feature Detection Approach for COVID-19 Classification based on X-ray Images

Noor, A., Pattanaik, P. A., Khan, M. Z., Alromema, W., & Noor, T. H. (2023) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2023.0140514 · Cited by 4

Multiresolution analysis for COVID-19 diagnosis from chest CT images: wavelet vs. contourlet transforms

Abdel‐Hamid, L. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-15485-9 · Cited by 5

Automated Diagnosis of COVID-19 Using Synthetic Chest X-Ray Images from Generative Adversarial Networks and Blend of Inception-v3 and Vgg-19 Features

Mahanta, D., Hazarika, D., & Nath, V. K. (2023) · SN Computer Science · doi:10.1007/s42979-023-02002-w · Cited by 3

Post-COVID effect on heart after recovery based on hybrid EfficientNet-DBN with multilevel classification using ECG images

Khan, M. A. B. A., & Reddy, E. S. (2024) · EngMedicine · doi:10.1016/j.engmed.2024.100021 · Cited by 3

Covid-19 Diagnosis by Gray-level Cooccurrence Matrix and Genetic Algorithm

Jiang, X., Brown, M., Hu, Z., & Cheong, H.-R. (2022) · ICST Transactions on e-Education and e-Learning · doi:10.4108/eetel.v8i1.2344 · Cited by 3

A novel hybrid approach for feature selection enhancement: COVID-19 case study

Limam, H., Hasni, O., & Alaya, I. B. (2022) · Computer Methods in Biomechanics & Biomedical Engineering · doi:10.1080/10255842.2022.2112185 · Cited by 3

COVID ‐19: A systematic review of prediction and classification techniques

Varma, O. R., Kalra, M., & Kirmani, S. (2023) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22905 · Cited by 3

Classification of COVID-19 Data Using Decision Tree Optimized with Particle Swarm Optimization and Genetic Algorithm

Rahmadeyan, A., Mustakim, M., Ocviani, R., Sarah, S., & Ardiansyah, F. (2024) · ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS) · doi:10.1109/icetsis61505.2024.10459540 · Cited by 3

Generative AI in Pandemic Prediction

Tavana, P., & ZareiNejad, M. (2025) · Springer eBooks · doi:10.1007/978-3-031-82963-5_2 · Cited by 3

A novel and ultralight convolutional neural network model for real-time detection of infectious lung diseases

Alqaissi, E. (2025) · Digital Health · doi:10.1177/20552076251318155 · Cited by 3

Two-Parallel-Step CNN Framework for Detection of COVID-19 Based on Segmented CT-Scan and Chest X-Ray Images

Bahroun, S. (2025) · Vietnam Journal of Computer Science · doi:10.1142/s219688882550006x · Cited by 3

Editorial for the Special Issue “Advances in Medical Image Processing, Segmentation, and Classification”

Mustafa, W. A., & Alquran, H. (2025) · Diagnostics · doi:10.3390/diagnostics15091114 · Cited by 3

Early prediction of bronchopulmonary dysplasia in preterm infants using chest X-rays through a comparative analysis of 13 CNN models across different post-birth days

Ali, M. A. M., Maeda, R., Fujita, D., Miyahara, N., Namba, F., & Kobashi, S. (2025) · Discover Computing · doi:10.1007/s10791-025-09519-z · Cited by 2

Hybrid deep learning system combining radiological and clinical data for improved tuberculosis diagnosis

Pokale, N. B., Shrivastav, A., Doke, K. K., Kataria, B., Shrivastav, R., & Shirkande, A. S. (2025) · Indian Journal of Tuberculosis · doi:10.1016/j.ijtb.2025.11.006 · Cited by 2

The effect of spatial and intensity level augmentation of structural magnetic resonance images on autism diagnosis model

Sujana, D. S., & Augustine, D. P. (2026) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2026.104830 · Cited by 2

Optimized Deep Learning for COVID-19 Chest Imaging with Broader Chest Disease Context: A Comprehensive Review

Houssein, E. H., Dirar, A., Ibrahim, I. A., & Al-Sayed, M. M. (2026) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-026-10628-1 · Cited by 2

FMD-UNet: fine-grained feature squeeze and multiscale cascade dilated semantic aggregation dual-decoder UNet for COVID-19 lung infection segmentation from CT images

Wang, W., Mao, Q., Tian, Y., Zhang, Y., Xiang, Z., & Ren, L. (2024) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/ad6f12 · Cited by 2

Image classification with deconvolution operation and augmentation

Sarkar, N. K., Singh, M. M., & Nandi, U. (2024) · The Computer Journal · doi:10.1093/comjnl/bxae099 · Cited by 2

Optimizing pulmonary chest x-ray classification with stacked feature ensemble and swin transformer integration

Mohanty, M. R., Mallick, P. K., & Reddy, A. V. N. (2024) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/ad8c46 · Cited by 2

Characterization of Pulmonary Pathology in the Golden Syrian Hamster Model of COVID-19 Using Micro-Computed Tomography

Ramirez, J. A., Dunlap, M. D., Prosnitz, R., Watson, A., Montgomery, M. K., Gutman, M. R., Coskran, T., Levinson, S. L., Yang, K. L., Kanevsky, I., et al. (2024) · Toxicologic Pathology · doi:10.1177/01926233241300451 · Cited by 2

A Deep Learning-Based Multiple Lung Disease Prediction and Classification Using CT- Scan Images

Priya, V. H. D., & Juliet, A. V. (2025) · SN Computer Science · doi:10.1007/s42979-025-03915-4 · Cited by 2

Interactive framework for Covid-19 detection and segmentation with feedback facility for dynamically improved accuracy and trust

Sailunaz, K., Beştepe, D., Özyer, T., Rokne, J. G., & Alhajj, R. (2022) · PLoS ONE · doi:10.1371/journal.pone.0278487 · Cited by 2

SARS-CoV-2 Prediction Strategy Based on Classification Algorithms from a Full Blood Examination

Choukhan, C. F., Lasri, I., Hatimi, R. E., Lemnaouar, M. R., & Esghir, M. (2023) · The Scientific World JOURNAL · doi:10.1155/2023/3248192 · Cited by 2

Automatic Quantification of COVID-19 Pulmonary Edema by Self-supervised Contrastive Learning

Liang, Z., Xue, Z., Rajaraman, S., Yang, F., & Antani, S. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-44917-8_12 · Cited by 2

Deep Learning for Skin Lesion Segmentation: A Review and Outlook

Yang, W., Gao, J., Chen, J., Yang, M., Ma, J., Chen, B., & Sun, H. (2024) · Lecture notes in electrical engineering · doi:10.1007/978-981-99-7545-7_18 · Cited by 2

Predicting and diagnosis of COVID-19 based on IoT and machine learning algorithm

Ertam, F., & Kılınçer, İ. F. (2024) · Advances in computers · doi:10.1016/bs.adcom.2024.06.009 · Cited by 1

Fault Detection on Short-Haul or Highly Dynamic Flights Using Transient Flight Segments

Varchev, T., Mathes, J., Koch, C., & Staudacher, S. (2024) · Journal of Engineering for Gas Turbines and Power · doi:10.1115/1.4066251 · Cited by 1

Classification of Chest X-Ray Images Using CNN-Based Transfer Learning Models

Chen, D., & Yu, X. (2024) · IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS) · doi:10.1109/icpics62053.2024.10796305 · Cited by 1

Pneumonia Image Classification Based on Lightweight Mobile ViT Networks

Zheng, Z., Liang, E., Weng, Z., Li, J., & Zhang, Y. (2025) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.70153 · Cited by 1

AI-based Smart Detection of Hormonal Changes in Women using Pixel Intensity Analysis

Ashitha, E., Vasanthi, G., Selvan, M. P., Parthasarathy, K., Prince, P. G. K., & Jancy, S. (2025) · International Conference on Intelligent Sustainable Systems (ICISS) · doi:10.1109/iciss63372.2025.11076332 · Cited by 1

Robust X-ray Image Classification using Vision Transformers: A Comparative Study with Convolutional Neural Networks

Mohcen, D., Nadim, H., Neili, Z., Mansri, I., & Sundaraj, K. (2025) · International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA) · doi:10.1109/acdsa65407.2025.11166094 · Cited by 1

A comprehensive review of analyzing the chest X-ray images to detect COVID-19 infections using deep learning techniques

Subramaniam, K., Palanisamy, N., Sinnaswamy, R. A., Muthusamy, S., Mishra, O. P., Kumar, L. A., Ramamoorthi, P., Rajan, C. C. A., Thangavel, G., & Sundararajan, S. C. M. (2023) · Soft Computing · doi:10.1007/s00500-023-08561-7 · Cited by 31

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

Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A ReviewPreprint

Shoeibi, A., Khodatars, M., Jafari, M., Ghassemi, N., Sadeghi, D., Moridian, P., Khadem, A. A., Alizadehsani, R., Hussain, S., Zare, A., et al. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.10785 · Cited by 149

Deep Learning-Based Image Classification for COVID-19 Disease: A Comprehensive Review

Ghosh, S., Chhetri, Y., Das, K., Mitra, A., Dutta, P., & Adak, P. (2026) · Cureus Journal of Computer Science. · doi:10.7759/s44389-026-00286-6

Application of deep learning techniques for detection of COVID-19 cases using chest X-ray images: A comprehensive study

Nayak, S. R., Nayak, D. R., Sinha, U., Arora, V., & Pachori, R. B. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.102365 · Cited by 401