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For: Liang S, Liu H, Gu Y, Guo X, Li H, Li L, Wu Z, Liu M, Tao L. Fast automated detection of COVID-19 from medical images using convolutional neural networks. Commun Biol 2021;4:35. [PMID: 33398067 DOI: 10.1038/s42003-020-01535-7] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 6.0] [Reference Citation Analysis]
Number Citing Articles
1 Zhang H, Liang W, Li C, Xiong Q, Shi H, Hu L, Li G. DCML: Deep contrastive mutual learning for COVID-19 recognition. Biomedical Signal Processing and Control 2022;77:103770. [DOI: 10.1016/j.bspc.2022.103770] [Reference Citation Analysis]
2 Yu D, Gu Y. A Machine Learning Method for the Fine-Grained Classification of Green Tea with Geographical Indication Using a MOS-Based Electronic Nose. Foods 2021;10:795. [PMID: 33917735 DOI: 10.3390/foods10040795] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Filchakova O, Dossym D, Ilyas A, Kuanysheva T, Abdizhamil A, Bukasov R. Review of COVID-19 testing and diagnostic methods. Talanta 2022;244:123409. [DOI: 10.1016/j.talanta.2022.123409] [Reference Citation Analysis]
4 Guan Y, Aamir M, Rahman Z, Ali A, Abro WA, Dayo ZA, Bhutta MS, Hu Z. A framework for efficient brain tumor classification using MRI images. Math Biosci Eng 2021;18:5790-815. [PMID: 34517512 DOI: 10.3934/mbe.2021292] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Abdeldayem OM, Dabbish AM, Habashy MM, Mostafa MK, Elhefnawy M, Amin L, Al-Sakkari EG, Ragab A, Rene ER. Viral outbreaks detection and surveillance using wastewater-based epidemiology, viral air sampling, and machine learning techniques: A comprehensive review and outlook. Sci Total Environ 2022;803:149834. [PMID: 34525746 DOI: 10.1016/j.scitotenv.2021.149834] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
6 Gillman AG, Lunardo F, Prinable J, Belous G, Nicolson A, Min H, Terhorst A, Dowling JA. Automated COVID-19 diagnosis and prognosis with medical imaging and who is publishing: a systematic review. Phys Eng Sci Med 2021. [PMID: 34919204 DOI: 10.1007/s13246-021-01093-0] [Reference Citation Analysis]
7 Naseer A, Tamoor M, Azhar A. Computer-aided COVID-19 diagnosis and a comparison of deep learners using augmented CXRs. J Xray Sci Technol 2021. [PMID: 34842222 DOI: 10.3233/XST-211047] [Reference Citation Analysis]
8 Umer MJ, Amin J, Sharif M, Anjum MA, Azam F, Shah JH. An integrated framework for COVID-19 classification based on classical and quantum transfer learning from a chest radiograph. Concurr Comput 2021;:e6434. [PMID: 34512201 DOI: 10.1002/cpe.6434] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
9 Hofer S, Hofstätter N, Duschl A, Himly M. SARS-CoV-2-Laden Respiratory Aerosol Deposition in the Lung Alveolar-Interstitial Region Is a Potential Risk Factor for Severe Disease: A Modeling Study. J Pers Med 2021;11:431. [PMID: 34069409 DOI: 10.3390/jpm11050431] [Reference Citation Analysis]
10 Khan M, Mehran MT, Haq ZU, Ullah Z, Naqvi SR, Ihsan M, Abbass H. Applications of artificial intelligence in COVID-19 pandemic: A comprehensive review. Expert Syst Appl 2021;185:115695. [PMID: 34400854 DOI: 10.1016/j.eswa.2021.115695] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]