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For: Khemasuwan D, Sorensen JS, Colt HG. Artificial intelligence in pulmonary medicine: computer vision, predictive model and COVID-19. Eur Respir Rev 2020;29:200181. [PMID: 33004526 DOI: 10.1183/16000617.0181-2020] [Cited by in Crossref: 24] [Cited by in F6Publishing: 24] [Article Influence: 8.0] [Reference Citation Analysis]
Number Citing Articles
1 Ekingen E, Teleş M, Yıldız A, Yıldırım M. Mediating effect of work stress in the relationship between fear of COVID-19 and nurses' organizational and professional turnover intentions. Arch Psychiatr Nurs 2023;42:97-105. [PMID: 36842836 DOI: 10.1016/j.apnu.2022.12.027] [Reference Citation Analysis]
2 Majeed A, Zhang X. On the Adoption of Modern Technologies to Fight the COVID-19 Pandemic: A Technical Synthesis of Latest Developments. COVID 2023;3:90-123. [DOI: 10.3390/covid3010006] [Reference Citation Analysis]
3 Gupta M, Kalra R. Role of Digital Healthcare in Rehabilitation During a Pandemic. System Design for Epidemics Using Machine Learning and Deep Learning 2023. [DOI: 10.1007/978-3-031-19752-9_16] [Reference Citation Analysis]
4 Hasanzadeh A, Hamblin MR, Kiani J, Noori H, Hardie JM, Karimi M, Shafiee H. Could artificial intelligence revolutionize the development of nanovectors for gene therapy and mRNA vaccines? Nano Today 2022;47:101665. [DOI: 10.1016/j.nantod.2022.101665] [Reference Citation Analysis]
5 Javidi H, Mariam A, Khademi G, Zabor EC, Zhao R, Radivoyevitch T, Rotroff DM. Identification of robust deep neural network models of longitudinal clinical measurements. NPJ Digit Med 2022;5:106. [PMID: 35896817 DOI: 10.1038/s41746-022-00651-4] [Reference Citation Analysis]
6 Hemalatha M. A Hybrid Random Forest Deep learning Classifier Empowered Edge Cloud Architecture for COVID-19 and Pneumonia Detection. Expert Syst Appl 2022;:118227. [PMID: 35880010 DOI: 10.1016/j.eswa.2022.118227] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Anand S, Sharma V, Pourush R, Jaiswal S. A comprehensive survey on the biomedical signal processing methods for the detection of COVID-19. Ann Med Surg (Lond) 2022;76:103519. [PMID: 35401978 DOI: 10.1016/j.amsu.2022.103519] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
8 Filipow N, Main E, Sebire NJ, Booth J, Taylor AM, Davies G, Stanojevic S. Implementation of prognostic machine learning algorithms in paediatric chronic respiratory conditions: a scoping review. BMJ Open Respir Res 2022;9:e001165. [PMID: 35297371 DOI: 10.1136/bmjresp-2021-001165] [Reference Citation Analysis]
9 Elhence A, Kohli V, Chamola V, Sikdar B. Enabling Cost-Effective and Secure Minor Medical Teleconsultation Using Artificial Intelligence and Blockchain. IEEE Internet Things M 2022;5:80-84. [DOI: 10.1109/iotm.001.2100142] [Reference Citation Analysis]
10 Choudhury S, Chohan A, Dadhwal R, Vakil AP, Franco R, Taweesedt PT. Applications of artificial intelligence in common pulmonary diseases. Artif Intell Med Imaging 2022; 3(1): 1-7 [DOI: 10.35711/aimi.v3.i1.1] [Reference Citation Analysis]
11 Taheri S, Asadizanjani N. An Overview of Medical Electronic Hardware Security and Emerging Solutions. Electronics 2022;11:610. [DOI: 10.3390/electronics11040610] [Reference Citation Analysis]
12 Karandashova S, Florova G, Idell S, Komissarov AA. From Bedside to the Bench—A Call for Novel Approaches to Prognostic Evaluation and Treatment of Empyema. Front Pharmacol 2022;12:806393. [DOI: 10.3389/fphar.2021.806393] [Reference Citation Analysis]
13 Cau R, Faa G, Nardi V, Balestrieri A, Puig J, Suri JS, Sanfilippo R, Saba L. Long-COVID diagnosis: from diagnostic to advanced AI-driven models. European Journal of Radiology 2022. [DOI: 10.1016/j.ejrad.2022.110164] [Cited by in Crossref: 10] [Cited by in F6Publishing: 10] [Article Influence: 10.0] [Reference Citation Analysis]
14 Khemasuwan D, Colt HG. Artificial intelligence and computational modeling. 3D Lung Models for Regenerating Lung Tissue 2022. [DOI: 10.1016/b978-0-323-90871-9.00010-3] [Reference Citation Analysis]
15 Maria A, Dimitrios V, Ioanna M, Charalampos M, Gerasimos M, Constantinos K. Clinical Decision Making and Outcome Prediction for COVID-19 Patients Using Machine Learning. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2022. [DOI: 10.1007/978-3-030-99194-4_1] [Reference Citation Analysis]
16 Liao KM, Liu CF, Chen CJ, Shen YT. Machine Learning Approaches for Predicting Acute Respiratory Failure, Ventilator Dependence, and Mortality in Chronic Obstructive Pulmonary Disease. Diagnostics (Basel) 2021;11:2396. [PMID: 34943632 DOI: 10.3390/diagnostics11122396] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
17 Brogi S, Calderone V. Artificial Intelligence in Translational Medicine. IJTM 2021;1:223-85. [DOI: 10.3390/ijtm1030016] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
18 Reier Forradellas RF, Garay Gallastegui LM. Digital Transformation and Artificial Intelligence Applied to Business: Legal Regulations, Economic Impact and Perspective. Laws 2021;10:70. [DOI: 10.3390/laws10030070] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
19 Darbari A, Kumar K, Darbari S, Patil PL. Requirement of artificial intelligence technology awareness for thoracic surgeons. Cardiothorac Surg 2021;29. [DOI: 10.1186/s43057-021-00053-4] [Cited by in Crossref: 6] [Cited by in F6Publishing: 8] [Article Influence: 3.0] [Reference Citation Analysis]
20 Afshar-Oromieh A, Prosch H, Schaefer-Prokop C, Bohn KP, Alberts I, Mingels C, Thurnher M, Cumming P, Shi K, Peters A, Geleff S, Lan X, Wang F, Huber A, Gräni C, Heverhagen JT, Rominger A, Fontanellaz M, Schöder H, Christe A, Mougiakakou S, Ebner L. A comprehensive review of imaging findings in COVID-19 - status in early 2021. Eur J Nucl Med Mol Imaging 2021;48:2500-24. [PMID: 33932183 DOI: 10.1007/s00259-021-05375-3] [Cited by in Crossref: 25] [Cited by in F6Publishing: 23] [Article Influence: 12.5] [Reference Citation Analysis]
21 Guo Z, Zhang J, Zuo Y, Liu P, Tang R, Li X. Channel Attention Residual Network for diagnosing Pneumonia. 2021 4th International Conference on Artificial Intelligence and Big Data (ICAIBD) 2021. [DOI: 10.1109/icaibd51990.2021.9459102] [Reference Citation Analysis]
22 Rolandsson Enes S, Krasnodembskaya AD, English K, Dos Santos CC, Weiss DJ. Research Progress on Strategies that can Enhance the Therapeutic Benefits of Mesenchymal Stromal Cells in Respiratory Diseases With a Specific Focus on Acute Respiratory Distress Syndrome and Other Inflammatory Lung Diseases. Front Pharmacol 2021;12:647652. [PMID: 33953680 DOI: 10.3389/fphar.2021.647652] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
23 Khemasuwan D, Colt HG. Applications and challenges of AI-based algorithms in the COVID-19 pandemic. BMJ Innov 2021;7:387-98. [DOI: 10.1136/bmjinnov-2020-000648] [Cited by in Crossref: 8] [Cited by in F6Publishing: 8] [Article Influence: 4.0] [Reference Citation Analysis]
24 Angelini E, Shah A. Using Artificial Intelligence in Fungal Lung Disease: CPA CT Imaging as an Example. Mycopathologia 2021. [PMID: 33840005 DOI: 10.1007/s11046-021-00546-0] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
25 Dwivedi K, Sharkey M, Condliffe R, Uthoff JM, Alabed S, Metherall P, Lu H, Wild JM, Hoffman EA, Swift AJ, Kiely DG. Pulmonary Hypertension in Association with Lung Disease: Quantitative CT and Artificial Intelligence to the Rescue? State-of-the-Art Review. Diagnostics (Basel) 2021;11:679. [PMID: 33918838 DOI: 10.3390/diagnostics11040679] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
26 Haleem A, Javaid M, Singh RP, Suman R. Applications of Artificial Intelligence (AI) for cardiology during COVID-19 pandemic. Sustainable Operations and Computers 2021;2:71-8. [DOI: 10.1016/j.susoc.2021.04.003] [Cited by in Crossref: 13] [Cited by in F6Publishing: 6] [Article Influence: 6.5] [Reference Citation Analysis]