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For: Jalaber C, Lapotre T, Morcet-Delattre T, Ribet F, Jouneau S, Lederlin M. Chest CT in COVID-19 pneumonia: A review of current knowledge. Diagn Interv Imaging. 2020;101:431-437. [PMID: 32571748 DOI: 10.1016/j.diii.2020.06.001] [Cited by in Crossref: 33] [Cited by in F6Publishing: 26] [Article Influence: 16.5] [Reference Citation Analysis]
Number Citing Articles
1 Martínez Chamorro E, Revilla Ostolaza T, Pérez Núñez M, Borruel Nacenta S, Cruz-conde Rodríguez-guerra C, Ibáñez Sanz L. Pulmonary embolisms in patients with COVID-19: A prevalence study in a tertiary hospital. Radiología (English Edition) 2021;63:13-21. [DOI: 10.1016/j.rxeng.2020.09.011] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Cabrelle G, Zanon C, Crimì F, Quaia E. Can chest computed tomography findings be compared between outpatient and hospitalized COVID‐19 patients? Journal of Medical Imaging and Radiation Sciences 2022. [DOI: 10.1016/j.jmir.2021.12.008] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Kato S, Ishiwata Y, Aoki R, Iwasawa T, Hagiwara E, Ogura T, Utsunomiya D. Imaging of COVID-19: An update of current evidences. Diagn Interv Imaging 2021;102:493-500. [PMID: 34088635 DOI: 10.1016/j.diii.2021.05.006] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
4 Bao C, Li Y, Liu J. Response to "Tomographic Findings and Thrombogenic Effects of COVID-19". J Am Coll Radiol 2020;17:1546. [PMID: 33137297 DOI: 10.1016/j.jacr.2020.08.023] [Reference Citation Analysis]
5 Ippolito D, Capodaglio C, Maino C, Corso R, Leni D, Fior D, Giandola T, Ragusi M, Talei Franzesi C, Gandola D, Rovere A, Sironi S. Compressive ultrasound can predict early pulmonary embolism onset in COVID patients. J Ultrasound 2022. [PMID: 35000130 DOI: 10.1007/s40477-021-00625-4] [Reference Citation Analysis]
6 Machnicki S, Patel D, Singh A, Talwar A, Mina B, Oks M, Makkar P, Naidich D, Mehta A, Hill NS, Brown KK, Raoof S. The Usefulness of Chest CT Imaging in Patients With Suspected or Diagnosed COVID-19: A Review of Literature. Chest 2021;160:652-70. [PMID: 33861993 DOI: 10.1016/j.chest.2021.04.004] [Reference Citation Analysis]
7 Scharf G, Meiler S, Zeman F, Schaible J, Poschenrieder F, Knobloch C, Kleine H, Scharf SE, Dinkel J, Stroszczynski C, Zorger N, Hamer OW. Combined Model of Quantitative Evaluation of Chest Computed Tomography and Laboratory Values for Assessing the Prognosis of Coronavirus Disease 2019. Rofo 2022. [PMID: 35272354 DOI: 10.1055/a-1731-7905] [Reference Citation Analysis]
8 Clementi N, Ghosh S, De Santis M, Castelli M, Criscuolo E, Zanoni I, Clementi M, Mancini N. Viral Respiratory Pathogens and Lung Injury. Clin Microbiol Rev 2021;34:e00103-20. [PMID: 33789928 DOI: 10.1128/CMR.00103-20] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
9 Weisberg EM, Chu LC, Rowe SP, Fishman EK. Radiology, COVID-19, and the next pandemic. Diagn Interv Imaging 2021:S2211-5684(21)00173-X. [PMID: 34366262 DOI: 10.1016/j.diii.2021.07.004] [Reference Citation Analysis]
10 Martínez Chamorro E, Revilla Ostolaza TY, Pérez Núñez M, Borruel Nacenta S, Cruz-Conde Rodríguez-Guerra C, Ibáñez Sanz L. Pulmonary embolisms in patients with COVID-19: a prevalence study in a tertiary hospital. Radiologia (Engl Ed) 2021;63:13-21. [PMID: 33228959 DOI: 10.1016/j.rx.2020.09.010] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
11 Chassagnon G, Regard L, Soyer P, Revel MP. COVID-19 after 18 months: Where do we stand? Diagn Interv Imaging 2021;102:491-2. [PMID: 34183299 DOI: 10.1016/j.diii.2021.06.003] [Reference Citation Analysis]
12 Si-Mohamed S, Boccalini S, Rodesch PA, Dessouky R, Lahoud E, Broussaud T, Sigovan M, Gamondes D, Coulon P, Yagil Y, Boussel L, Douek P. Feasibility of lung imaging with a large field-of-view spectral photon-counting CT system. Diagn Interv Imaging 2021;102:305-12. [PMID: 33610503 DOI: 10.1016/j.diii.2021.01.001] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
13 Trunz LM, Lee P, Lange SM, Pomeranz CL, Needleman L, Ford RW, Karambelkar A, Sundaram B. Imaging approach to COVID-19 associated pulmonary embolism. Int J Clin Pract 2021;:e14340. [PMID: 33966326 DOI: 10.1111/ijcp.14340] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
14 Başaran S, Şimşek-Yavuz S, Meşe S, Çağatay A, Medetalibeyoğlu A, Öncül O, Özsüt H, Ağaçfidan A, Gül A, Eraksoy H. The effect of tocilizumab, anakinra and prednisolone on antibody response to SARS-CoV-2 in patients with COVID-19: A prospective cohort study with multivariate analysis of factors affecting the antibody response. Int J Infect Dis 2021;105:756-62. [PMID: 33737128 DOI: 10.1016/j.ijid.2021.03.031] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
15 Bougourzi F, Distante C, Ouafi A, Dornaika F, Hadid A, Taleb-Ahmed A. Per-COVID-19: A Benchmark Dataset for COVID-19 Percentage Estimation from CT-Scans. J Imaging 2021;7:189. [PMID: 34564115 DOI: 10.3390/jimaging7090189] [Reference Citation Analysis]
16 Boulanger H, Saksi SA, Achiche J, Batusanski F, Stawiarski N, Diddaoui A, Fromentin L, Chawki M. SARS-CoV-2 Antibodies in Hemodialysis Patients Six Months after Infection Compared to Healthcare Workers. Int J Nephrol 2021;2021:4747221. [PMID: 34868683 DOI: 10.1155/2021/4747221] [Reference Citation Analysis]
17 Guiot J, Vaidyanathan A, Deprez L, Zerka F, Danthine D, Frix AN, Thys M, Henket M, Canivet G, Mathieu S, Eftaxia E, Lambin P, Tsoutzidis N, Miraglio B, Walsh S, Moutschen M, Louis R, Meunier P, Vos W, Leijenaar RTH, Lovinfosse P. Development and Validation of an Automated Radiomic CT Signature for Detecting COVID-19. Diagnostics (Basel) 2020;11:E41. [PMID: 33396587 DOI: 10.3390/diagnostics11010041] [Cited by in Crossref: 5] [Cited by in F6Publishing: 8] [Article Influence: 2.5] [Reference Citation Analysis]
18 Eroglu SE, Algin A, Bulut SSD, Sakci Z, Aydin M, Aksel G, Altunok I, Akca HS, Bukte Y. Diagnostic performance of thorax CT in mildly symptomatic COVID-19 patients: The importance of atypical CT findings. North Clin Istanb 2021;8:425-34. [PMID: 34909580 DOI: 10.14744/nci.2021.81557] [Reference Citation Analysis]
19 Rorat M, Jurek T, Simon K, Guziński M. Value of quantitative analysis in lung computed tomography in patients severely ill with COVID-19. PLoS One 2021;16:e0251946. [PMID: 34015025 DOI: 10.1371/journal.pone.0251946] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
20 Jemioło P, Storman D, Orzechowski P. Artificial Intelligence for COVID-19 Detection in Medical Imaging—Diagnostic Measures and Wasting—A Systematic Umbrella Review. JCM 2022;11:2054. [DOI: 10.3390/jcm11072054] [Reference Citation Analysis]
21 Bhandari S, Singh S, Tak A, Patel B, Gupta J, Gupta K, Kakkar S, Darshan S, Arora A, Dube A. Independent role of CT chest scan in COVID-19 prognosis: Evidence from the machine learning classification. Scripta Medica 2021;52:273-8. [DOI: 10.5937/scriptamed52-34457] [Reference Citation Analysis]
22 Zella D, Giovanetti M, Cella E, Borsetti A, Ciotti M, Ceccarelli G, D'Ettorre G, Pezzuto A, Tambone V, Campanozzi L, Magheri M, Unali F, Bianchi M, Benedetti F, Pascarella S, Angeletti S, Ciccozzi M. The importance of genomic analysis in cracking the coronavirus pandemic. Expert Rev Mol Diagn 2021;21:547-62. [PMID: 33849359 DOI: 10.1080/14737159.2021.1917998] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
23 Ohana M, Muller J, Severac F, Bilbault P, Behr M, Oberlin M, Leyendecker P, Roy C. Temporal variations in the diagnostic performance of chest CT for Covid-19 depending on disease prevalence: Experience from North-Eastern France. Eur J Radiol 2021;134:109425. [PMID: 33254065 DOI: 10.1016/j.ejrad.2020.109425] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
24 Görgün S, Cindoruk Ş, Özgen E, Yadigaroğlu M, Demir MT, Yücel M, Akpınar ÇK, Güzel M. Diagnostic and Prognostic Value of Serum Endocan Levels in Patients With COVID-19. Angiology 2021;:33197211026044. [PMID: 34180269 DOI: 10.1177/00033197211026044] [Reference Citation Analysis]
25 Gaudêncio AS, Vaz PG, Hilal M, Mahé G, Lederlin M, Humeau-Heurtier A, Cardoso JM. Evaluation of COVID-19 chest computed tomography: A texture analysis based on three-dimensional entropy. Biomed Signal Process Control 2021;68:102582. [PMID: 33824680 DOI: 10.1016/j.bspc.2021.102582] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
26 Khamis F, Al Awaidy S, Shaaibi MA, Shukeili MA, Chhetri S, Balushi AA, Sulaimi SA, Balushi AA, Wesonga R. Epidemiological Characteristics of Hospitalized Patients with Moderate versus Severe COVID-19 Infection: A Retrospective Cohort Single Centre Study. Diseases 2021;10:1. [PMID: 35076497 DOI: 10.3390/diseases10010001] [Reference Citation Analysis]
27 Jalaber C, Chassagnon G, Hani C, Dangeard S, Babin M, Launay O, Revel MP. Is COVID-19 pneumonia differentiable from other viral pneumonia on CT scan? Respir Med Res 2021;79:100824. [PMID: 33971431 DOI: 10.1016/j.resmer.2021.100824] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
28 Revel MP. COVID-19 pneumonia: The fight must go on. Diagn Interv Imaging 2021;102:61-2. [PMID: 33494861 DOI: 10.1016/j.diii.2021.01.006] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
29 Rea G, Lassandro F, Lieto R, Bocchini G, Romano F, Sica G, Valente T, Muto E, Murino P, Pinto A, Montesarchio V, Muto M, Pacella D, Capitelli L, Bocchino M. Lesson by SARS-CoV-2 disease (COVID-19): whole-body CT angiography detection of "relevant" and "other/incidental" systemic vascular findings. Eur Radiol 2021. [PMID: 33864140 DOI: 10.1007/s00330-021-07904-y] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
30 Peng Y, Liu E, Peng S, Chen Q, Li D, Lian D. Using artificial intelligence technology to fight COVID-19: a review. Artif Intell Rev 2022;:1-37. [PMID: 35002010 DOI: 10.1007/s10462-021-10106-z] [Reference Citation Analysis]
31 Garin A, Chassagnon G, Tual A, Revel MP. CT features of fibrosing mediastinitis. Diagn Interv Imaging 2021:S2211-5684(21)00143-1. [PMID: 34167927 DOI: 10.1016/j.diii.2021.05.013] [Reference Citation Analysis]
32 Lee KK, Rahimi O, Lee CK, Shafi A, Hawwass D. A Meta-Analysis: Coronary Artery Calcium Score and COVID-19 Prognosis. Medical Sciences 2022;10:5. [DOI: 10.3390/medsci10010005] [Reference Citation Analysis]
33 Malécot N, Chrusciel J, Sanchez S, Sellès P, Goetz C, Leveque H, Parizel E, Pradel J, Mahna MA, Bouvier E, Uyttenhove F, Bonnefoy E, Vazquez G, Adib O, Calvo P, Antoine C, Jullien V, Cirille S, Dumas A, Defasque A, Ghorbal YB, Elkadri M, Schertz M, Cavet M. Chest CT characteristics are strongly predictive of mortality in patients with COVID-19 pneumonia: A multicentric cohort study. Academic Radiology 2022. [DOI: 10.1016/j.acra.2022.01.010] [Reference Citation Analysis]
34 Campos-Ferreira D, Visani V, Córdula C, Nascimento GA, Montenegro LML, Schindler HC, Cavalcanti IMF. COVID-19 challenges: From SARS-CoV-2 infection to effective point-of-care diagnosis by electrochemical biosensing platforms. Biochem Eng J 2021;176:108200. [PMID: 34522158 DOI: 10.1016/j.bej.2021.108200] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
35 Geng MJ, Wang LP, Ren X, Yu JX, Chang ZR, Zheng CJ, An ZJ, Li Y, Yang XK, Zhao HT, Li ZJ, He GX, Feng ZJ. Risk factors for developing severe COVID-19 in China: an analysis of disease surveillance data. Infect Dis Poverty 2021;10:48. [PMID: 33845915 DOI: 10.1186/s40249-021-00820-9] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
36 Rasheed J, Jamil A, Hameed AA, Al-Turjman F, Rasheed A. COVID-19 in the Age of Artificial Intelligence: A Comprehensive Review. Interdiscip Sci 2021;13:153-75. [PMID: 33886097 DOI: 10.1007/s12539-021-00431-w] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
37 Li J, Long X, Wang X, Fang F, Lv X, Zhang D, Sun Y, Hu S, Lin Z, Xiong N. Radiology indispensable for tracking COVID-19. Diagn Interv Imaging 2021;102:69-75. [PMID: 33281082 DOI: 10.1016/j.diii.2020.11.008] [Cited by in Crossref: 6] [Cited by in F6Publishing: 7] [Article Influence: 3.0] [Reference Citation Analysis]
38 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]
39 Alqahtani JS, Alghamdi SM, Aldhahir AM, Althobiani M, Raya RP, Oyelade T. Thoracic imaging outcomes in COVID-19 survivors. World J Radiol 2021; 13(6): 149-156 [PMID: 34249236 DOI: 10.4329/wjr.v13.i6.149] [Reference Citation Analysis]
40 Devie A, Kanagaratnam L, Perotin JM, Jolly D, Ravey JN, Djelouah M, Hoeffel C. COVID-19: A qualitative chest CT model to identify severe form of the disease. Diagn Interv Imaging 2021;102:77-84. [PMID: 33419693 DOI: 10.1016/j.diii.2020.12.002] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
41 Hoang-Thi TN, Vakalopoulou M, Christodoulidis S, Paragios N, Revel MP, Chassagnon G. Deep learning for lung disease segmentation on CT: Which reconstruction kernel should be used? Diagn Interv Imaging 2021;102:691-5. [PMID: 34686464 DOI: 10.1016/j.diii.2021.10.001] [Reference Citation Analysis]