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For: Suri JS, Agarwal S, Gupta SK, Puvvula A, Biswas M, Saba L, Bit A, Tandel GS, Agarwal M, Patrick A, Faa G, Singh IM, Oberleitner R, Turk M, Chadha PS, Johri AM, Miguel Sanches J, 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, Ahluwalia P, Teji J, Al-Maini M, Dhanjil SK, Sockalingam M, Saxena A, Nicolaides A, Sharma A, Rathore V, Ajuluchukwu JNA, Fatemi M, Alizad A, Viswanathan V, Krishnan PK, Naidu S. A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence. Comput Biol Med 2021;130:104210. [PMID: 33550068 DOI: 10.1016/j.compbiomed.2021.104210] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 5.0] [Reference Citation Analysis]
Number Citing Articles
1 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]
2 Suri JS, Paul S, Maindarkar MA, Puvvula A, Saxena S, Saba L, Turk M, Laird JR, Khanna NN, Viskovic K, Singh IM, Kalra M, Krishnan PR, Johri A, Paraskevas KI. Cardiovascular/Stroke Risk Stratification in Parkinson’s Disease Patients Using Atherosclerosis Pathway and Artificial Intelligence Paradigm: A Systematic Review. Metabolites 2022;12:312. [DOI: 10.3390/metabo12040312] [Reference Citation Analysis]
3 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]
4 Skandha SS, Nicolaides A, Gupta SK, Koppula VK, Saba L, Johri AM, Kalra MS, Suri JS. A hybrid deep learning paradigm for carotid plaque tissue characterization and its validation in multicenter cohorts using a supercomputer framework. Comput Biol Med 2021;141:105131. [PMID: 34922173 DOI: 10.1016/j.compbiomed.2021.105131] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
5 Bouchareb Y, Moradi Khaniabadi P, Al Kindi F, Al Dhuhli H, Shiri I, Zaidi H, Rahmim A. Artificial intelligence-driven assessment of radiological images for COVID-19. Comput Biol Med 2021;136:104665. [PMID: 34343890 DOI: 10.1016/j.compbiomed.2021.104665] [Reference Citation Analysis]
6 Agarwal M, Agarwal S, Saba L, Chabert GL, Gupta S, Carriero A, Pasche A, Danna P, Mehmedovic A, Faa G, Shrivastava S, Jain K, Jain H, Jujaray T, Singh IM, Turk M, Chadha PS, Johri AM, Khanna NN, Mavrogeni S, Laird JR, Sobel DW, Miner M, Balestrieri A, Sfikakis PP, Tsoulfas G, 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, Yadav RR, Nagy F, Kincses ZT, Ruzsa Z, Naidu S, Viskovic K, Kalra MK, Suri JS. Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0. Computers in Biology and Medicine 2022;146:105571. [DOI: 10.1016/j.compbiomed.2022.105571] [Reference Citation Analysis]
7 Khanna NN, Maindarkar M, Saxena A, Ahluwalia P, Paul S, Srivastava SK, Cuadrado-godia E, Sharma A, Omerzu T, Saba L, Mavrogeni S, Turk M, Laird JR, Kitas GD, Fatemi M, Barqawi AB, Miner M, Singh IM, Johri A, Kalra MM, Agarwal V, Paraskevas KI, Teji JS, Fouda MM, Pareek G, Suri JS. Cardiovascular/Stroke Risk Assessment in Patients with Erectile Dysfunction—A Role of Carotid Wall Arterial Imaging and Plaque Tissue Characterization Using Artificial Intelligence Paradigm: A Narrative Review. Diagnostics 2022;12:1249. [DOI: 10.3390/diagnostics12051249] [Reference Citation Analysis]
8 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]
9 Li K, Zhang C, Qin L, Zang C, Li A, Sun J, Zhao Y, Feng Y, Zhang Y. A Nomogram Prediction of Length of Hospital Stay in Patients with COVID-19 Pneumonia: A Retrospective Cohort Study. Dis Markers 2021;2021:5598824. [PMID: 34158873 DOI: 10.1155/2021/5598824] [Reference Citation Analysis]
10 Haimovich AD, Jiang R, Taylor RA, Belsky JB. Risk factor identification and predictive models for central line requirements for patients on vasopressors. Anaesth Intensive Care 2021;49:275-83. [PMID: 34392707 DOI: 10.1177/0310057X211024258] [Reference Citation Analysis]
11 Wong PK, Yan T, Wang H, Chan IN, Wang J, Li Y, Ren H, Wong CH. Automatic detection of multiple types of pneumonia: Open dataset and a multi-scale attention network. Biomed Signal Process Control 2022;73:103415. [PMID: 34909050 DOI: 10.1016/j.bspc.2021.103415] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
12 David S, Dorado G, Duarte EL, David-bosne S, Trigueiro-louro J, Rebelo-de-andrade H. COVID-19: impact on Public Health and hypothesis-driven investigations on genetic susceptibility and severity. Immunogenetics. [DOI: 10.1007/s00251-022-01261-w] [Reference Citation Analysis]
13 Patel R, Kaki M, Potluri VS, Kahar P, Khanna D. A comprehensive review of SARS-CoV-2 vaccines: Pfizer, Moderna & Johnson & Johnson. Hum Vaccin Immunother 2022;:1-12. [PMID: 35130825 DOI: 10.1080/21645515.2021.2002083] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 7.0] [Reference Citation Analysis]
14 Cheng Y, Li J, Chen M, Zhang S, He R, Wang N. Environmentally friendly and antimicrobial bilayer structured fabrics with integrated interception and sterilization for personal protective mask. Separation and Purification Technology 2022;294:121165. [DOI: 10.1016/j.seppur.2022.121165] [Reference Citation Analysis]
15 Larijani B, Foroughi-Heravani N, Abedi M, Tayanloo-Beik A, Rezaei-Tavirani M, Adibi H, Arjmand B. Recent Advances of COVID-19 Modeling Based on Regenerative Medicine. Front Cell Dev Biol 2021;9:683619. [PMID: 34760882 DOI: 10.3389/fcell.2021.683619] [Reference Citation Analysis]
16 Granata V, Ianniello S, Fusco R, Urraro F, Pupo D, Magliocchetti S, Albarello F, Campioni P, Cristofaro M, Di Stefano F, Fusco N, Petrone A, Schininà V, Villanacci A, Grassi F, Grassi R, Grassi R. Quantitative Analysis of Residual COVID-19 Lung CT Features: Consistency among Two Commercial Software. J Pers Med 2021;11:1103. [PMID: 34834455 DOI: 10.3390/jpm11111103] [Reference Citation Analysis]
17 Álvarez-Rodríguez L, Moura J, Novo J, Ortega M. Does imbalance in chest X-ray datasets produce biased deep learning approaches for COVID-19 screening? BMC Med Res Methodol 2022;22:125. [PMID: 35484483 DOI: 10.1186/s12874-022-01578-w] [Reference Citation Analysis]
18 Das S, Nayak G, Saba L, Kalra M, Suri JS, Saxena S. An artificial intelligence framework and its bias for brain tumor segmentation: A narrative review. Computers in Biology and Medicine 2022. [DOI: 10.1016/j.compbiomed.2022.105273] [Cited by in Crossref: 3] [Article Influence: 3.0] [Reference Citation Analysis]