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For: Chaddad A, Hassan L, Desrosiers C. Deep CNN models for predicting COVID-19 in CT and x-ray images. J Med Imaging (Bellingham) 2021;8:014502. [PMID: 33912622 DOI: 10.1117/1.JMI.8.S1.014502] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Ali Ahmed SA, Yavuz MC, Sen MU, Gulsen F, Tutar O, Korkmazer B, Samanci C, Şirolu S, Hamid R, Eryürekli AE, Mammadov T, Yanikoglu B. Comparison and Ensemble of 2D and 3D Approaches for COVID-19 Detection in CT Images. Neurocomputing 2022. [DOI: 10.1016/j.neucom.2022.02.018] [Reference Citation Analysis]
2 Suri JS, Agarwal S, Elavarthi P, Pathak R, Ketireddy V, Columbu M, Saba L, Gupta SK, Faa G, Singh IM, Turk M, Chadha PS, Johri AM, Khanna NN, Viskovic K, Mavrogeni S, Laird JR, Pareek G, Miner M, Sobel DW, Balestrieri A, Sfikakis PP, Tsoulfas G, Protogerou A, Misra DP, Agarwal V, Kitas GD, Teji JS, Al-Maini M, Dhanjil SK, Nicolaides A, Sharma A, Rathore V, Fatemi M, Alizad A, Krishnan PR, Ferenc N, Ruzsa Z, Gupta A, Naidu S, Kalra MK. Inter-Variability Study of COVLIAS 1.0: Hybrid Deep Learning Models for COVID-19 Lung Segmentation in Computed Tomography. Diagnostics (Basel) 2021;11:2025. [PMID: 34829372 DOI: 10.3390/diagnostics11112025] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Toğaçar M, Muzoğlu N, Ergen B, Yarman BSB, Halefoğlu AM. Detection of COVID-19 findings by the local interpretable model-agnostic explanations method of types-based activations extracted from CNNs. Biomed Signal Process Control 2022;71:103128. [PMID: 34490055 DOI: 10.1016/j.bspc.2021.103128] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Suri JS, Agarwal S, Carriero A, Paschè A, Danna PSC, Columbu M, Saba L, Viskovic K, Mehmedović A, Agarwal S, Gupta L, Faa G, Singh IM, Turk M, Chadha PS, Johri AM, Khanna NN, Mavrogeni S, Laird JR, Pareek G, Miner M, Sobel DW, Balestrieri A, Sfikakis PP, Tsoulfas G, Protogerou A, Misra DP, Agarwal V, Kitas GD, Teji JS, Al-maini M, Dhanjil SK, Nicolaides A, Sharma A, Rathore V, Fatemi M, Alizad A, Krishnan PR, Nagy F, Ruzsa Z, Gupta A, Naidu S, Paraskevas KI, Kalra MK. COVLIAS 1.0 vs. MedSeg: Artificial Intelligence-Based Comparative Study for Automated COVID-19 Computed Tomography Lung Segmentation in Italian and Croatian Cohorts. Diagnostics 2021;11:2367. [DOI: 10.3390/diagnostics11122367] [Reference Citation Analysis]
5 Suri JS, Agarwal S, Pathak R, Ketireddy V, Columbu M, Saba L, Gupta SK, Faa G, Singh IM, Turk M, Chadha PS, Johri AM, Khanna NN, Viskovic K, Mavrogeni S, Laird JR, Pareek G, Miner M, Sobel DW, Balestrieri A, Sfikakis PP, Tsoulfas G, Protogerou A, Misra DP, Agarwal V, Kitas GD, Teji JS, Al-Maini M, Dhanjil SK, Nicolaides A, Sharma A, Rathore V, Fatemi M, Alizad A, Krishnan PR, Frence N, Ruzsa Z, Gupta A, Naidu S, Kalra M. COVLIAS 1.0: Lung Segmentation in COVID-19 Computed Tomography Scans Using Hybrid Deep Learning Artificial Intelligence Models. Diagnostics (Basel) 2021;11:1405. [PMID: 34441340 DOI: 10.3390/diagnostics11081405] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]