The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Deep learning approaches for COVID-19 detection based on chest X-ray images
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Automated detection of COVID-19 cases using deep neural networks with X-ray images
Ozturk, T., Talo, M., Yildirim, E. A., Baloglu, U. B., Yildirim, O., & Rajendra Acharya, U. (2020) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2020.103792 · Cited by 2,594
Coronavirus disease (COVID-19) pandemic.
Rampal, L., & Liew, B. S. (2020) · PubMed · Cited by 2,116
Support vector machine in machine condition monitoring and fault diagnosis
Widodo, A., & Yang, B.-S. (2007) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2006.12.007 · Cited by 1,650
Rajpurkar, P., Irvin, J., Ball, R. L., Zhu, K., Yang, B., Mehta, H., Duan, T., Ding, D., Bagul, A., Langlotz, C. P., et al. (2018) · PLOS Medicine · doi:10.1371/journal.pmed.1002686 · Cited by 1,449
Representing shape with a spatial pyramid kernel
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Blur Insensitive Texture Classification Using Local Phase Quantization
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Cited by
Transfer learning techniques for medical image analysis: A review
Kora, P., Ooi, C. P., Faust, O., Raghavendra, U., Gudigar, A., Chan, W. Y., Meenakshi, K., Swaraja, K., Plawiak, P., & Rajendra Acharya, U. (2022) · Biocybernetics and Biomedical Engineering · doi:10.1016/j.bbe.2021.11.004 · Cited by 367
COVID-19 image classification using deep learning: Advances, challenges and opportunities
Aggarwal, P., Mishra, N. K., Fatimah, B., Singh, P., Gupta, A., & Joshi, S. D. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.105350 · Cited by 168
A Review of Recent Advances in Deep Learning Models for Chest Disease Detection Using Radiography
Ait Nasser, A., & Akhloufi, M. A. (2023) · Diagnostics · doi:10.3390/diagnostics13010159 · Cited by 121
Study on IoT for SARS-CoV-2 with healthcare: present and future perspective
Rahman, A., Department of Computer Science and Engineering, N. I. O. T. E. A. R. (., Rahman, M., Kundu, D., Karim, M. R., Band, S. S., Sookhak, M., Department of Computer Science and Engineering, M. B. S. A. T. U., Department of Electrical and Electronic Engineering, N. I. O. T. E. A. R. (., Future Technology Research Center, C. O. F., et al. (2021) · Mathematical Biosciences and Engineering · doi:10.3934/mbe.2021475 · Cited by 22
Ezzeddine, H., Awad, M., Ghanem, A. S. A., & Mourani, B. (2021) · 2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology (IMCET) · doi:10.1109/imcet53404.2021.9665574 · Cited by 2
Metadata
- Authors
- Ismael, A. M., & Şengür, A.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2021-02
- Volume
- 164
- Pages
- 114054
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W3089168916
- Cited by
- 746
- References
- 33
- FWCI
- 61.19
- Type
- journal article
- Language
- en
- Open access
- green
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- Ismael, A. M., & Şengür, A. (2021). Deep learning approaches for COVID-19 detection based on chest X-ray images. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2020.114054
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
