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For: Bragazzi NL, Dai H, Damiani G, Behzadifar M, Martini M, Wu J. How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic. Int J Environ Res Public Health. 2020;17. [PMID: 32370204 DOI: 10.3390/ijerph17093176] [Cited by in Crossref: 76] [Cited by in F6Publishing: 42] [Article Influence: 38.0] [Reference Citation Analysis]
Number Citing Articles
1 Comito C, Pizzuti C. Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review. Artificial Intelligence in Medicine 2022. [DOI: 10.1016/j.artmed.2022.102286] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
2 Abdulkareem M, Petersen SE. The Promise of AI in Detection, Diagnosis, and Epidemiology for Combating COVID-19: Beyond the Hype. Front Artif Intell 2021;4:652669. [PMID: 34056579 DOI: 10.3389/frai.2021.652669] [Reference Citation Analysis]
3 Asadzadeh A, Mohammadzadeh Z, Fathifar Z, Jahangiri-mirshekarlou S, Rezaei-hachesu P. A framework for information technology-based management against COVID-19 in Iran. BMC Public Health 2022;22. [DOI: 10.1186/s12889-022-12781-1] [Reference Citation Analysis]
4 Torre-Bastida AI, Díaz-de-Arcaya J, Osaba E, Muhammad K, Camacho D, Del Ser J. Bio-inspired computation for big data fusion, storage, processing, learning and visualization: state of the art and future directions. Neural Comput Appl 2021;:1-31. [PMID: 34366573 DOI: 10.1007/s00521-021-06332-9] [Reference Citation Analysis]
5 Bragazzi NL, Mansour M, Bonsignore A, Ciliberti R. The Role of Hospital and Community Pharmacists in the Management of COVID-19: Towards an Expanded Definition of the Roles, Responsibilities, and Duties of the Pharmacist. Pharmacy (Basel) 2020;8:E140. [PMID: 32784696 DOI: 10.3390/pharmacy8030140] [Cited by in Crossref: 24] [Cited by in F6Publishing: 14] [Article Influence: 12.0] [Reference Citation Analysis]
6 Liu F, Pan W. Risk Prediction of E-Payment by Big Data Management Technology. Mathematical Problems in Engineering 2022;2022:1-8. [DOI: 10.1155/2022/6815255] [Reference Citation Analysis]
7 Shahid O, Nasajpour M, Pouriyeh S, Parizi RM, Han M, Valero M, Li F, Aledhari M, Sheng QZ. Machine learning research towards combating COVID-19: Virus detection, spread prevention, and medical assistance. J Biomed Inform 2021;117:103751. [PMID: 33771732 DOI: 10.1016/j.jbi.2021.103751] [Cited by in Crossref: 3] [Article Influence: 3.0] [Reference Citation Analysis]
8 Jiang Y, Huang X, Li Z. Spatiotemporal Patterns of Human Mobility and Its Association with Land Use Types during COVID-19 in New York City. IJGI 2021;10:344. [DOI: 10.3390/ijgi10050344] [Cited by in Crossref: 9] [Cited by in F6Publishing: 5] [Article Influence: 9.0] [Reference Citation Analysis]
9 Nguyen DC, Ding M, Pathirana PN, Seneviratne A. Blockchain and AI-Based Solutions to Combat Coronavirus (COVID-19)-Like Epidemics: A Survey. IEEE Access 2021;9:95730-53. [PMID: 34812398 DOI: 10.1109/ACCESS.2021.3093633] [Cited by in Crossref: 10] [Cited by in F6Publishing: 2] [Article Influence: 10.0] [Reference Citation Analysis]
10 Rizzato VL, Lotto M, Lourenço Neto N, Oliveira TM, Cruvinel T. Digital surveillance: The interests in toothache-related information after the outbreak of COVID-19. Oral Dis 2021. [PMID: 34448289 DOI: 10.1111/odi.14012] [Reference Citation Analysis]
11 Wang Q, Zhang C. Can COVID-19 and environmental research in developing countries support these countries to meet the environmental challenges induced by the pandemic? Environ Sci Pollut Res Int 2021;28:41296-316. [PMID: 33782826 DOI: 10.1007/s11356-021-13591-5] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
12 Abdalla W, Renukappa S, Suresh S. Managing COVID‐19‐related knowledge: A smart cities perspective. Knowl Process Manag. [DOI: 10.1002/kpm.1706] [Reference Citation Analysis]
13 Saxena N, Gupta P, Raman R, Rathore AS. Role of data science in managing COVID-19 pandemic. Indian Chemical Engineer 2020;62:385-95. [DOI: 10.1080/00194506.2020.1855085] [Cited by in Crossref: 3] [Article Influence: 1.5] [Reference Citation Analysis]
14 Hoernke K. A socially just recovery from the COVID-19 pandemic: a call for action on the social determinants of urban health inequalities. J R Soc Med 2020;113:482-4. [PMID: 32915092 DOI: 10.1177/0141076820948817] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
15 Damiani G, Gironi LC, Kridin K, Pacifico A, Buja A, Bragazzi NL, Spalkowska M, Pigatto PDM, Santus P, Savoia P; Young Dermatologists Italian Network. Mask-induced Koebner phenomenon and its clinical phenotypes: A multicenter, real-life study focusing on 873 dermatological consultations during COVID-19 pandemics. Dermatol Ther 2021;34:e14823. [PMID: 33527560 DOI: 10.1111/dth.14823] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 6.0] [Reference Citation Analysis]
16 Liu L, Bi M, Wang Y, Liu J, Jiang X, Xu Z, Zhang X. Artificial intelligence-powered microfluidics for nanomedicine and materials synthesis. Nanoscale 2021;13:19352-66. [PMID: 34812823 DOI: 10.1039/d1nr06195j] [Reference Citation Analysis]
17 Kumar A, Pujari P, Gupta N. Artificial Intelligence: Technology 4.0 as a solution for healthcare workers during COVID-19 pandemic. Acta Univ Bohem Merid 2021;24:19-35. [DOI: 10.32725/acta.2021.002] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 4.0] [Reference Citation Analysis]
18 Gironi LC, Damiani G, Zavattaro E, Pacifico A, Santus P, Pigatto PDM, Cremona O, Savoia P. Tetracyclines in COVID-19 patients quarantined at home: Literature evidence supporting real-world data from a multicenter observational study targeting inflammatory and infectious dermatoses. Dermatol Ther 2021;34:e14694. [PMID: 33354849 DOI: 10.1111/dth.14694] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 2.5] [Reference Citation Analysis]
19 Bragazzi NL. Digital Technologies-Enabled Smart Manufacturing and Industry 4.0 in the Post-COVID-19 Era: Lessons Learnt from a Pandemic. Int J Environ Res Public Health 2020;17:E4785. [PMID: 32635191 DOI: 10.3390/ijerph17134785] [Cited by in Crossref: 11] [Cited by in F6Publishing: 3] [Article Influence: 5.5] [Reference Citation Analysis]
20 Wu J, Wang J, Nicholas S, Maitland E, Fan Q. Application of Big Data Technology for COVID-19 Prevention and Control in China: Lessons and Recommendations. J Med Internet Res 2020;22:e21980. [PMID: 33001836 DOI: 10.2196/21980] [Cited by in Crossref: 12] [Cited by in F6Publishing: 8] [Article Influence: 6.0] [Reference Citation Analysis]
21 Ilbeigipou S, Albadvi A. Symptom-based analysis of COVID-19 cases using supervised machine learning approaches to improve medical decision-making. Informatics in Medicine Unlocked 2022. [DOI: 10.1016/j.imu.2022.100933] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
22 Bardanzellu F, Fanos V, Marseglia GL. Metabolomics, Microbiomics, Machine learning during the COVID‐19 pandemic. Pediatric Allergy Immunology 2022;33:86-8. [DOI: 10.1111/pai.13640] [Reference Citation Analysis]
23 Cosoli G, Poli A, Scalise L, Spinsante S. Measurement of multimodal physiological signals for stimulation detection by wearable devices. Measurement 2021;184:109966. [DOI: 10.1016/j.measurement.2021.109966] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
24 Behl A, Gaur J, Pereira V, Yadav R, Laker B. Role of big data analytics capabilities to improve sustainable competitive advantage of MSME service firms during COVID-19 – A multi-theoretical approach. Journal of Business Research 2022;148:378-89. [DOI: 10.1016/j.jbusres.2022.05.009] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
25 Boza-kiss B, Pachauri S, Zimm C. Deprivations and Inequities in Cities Viewed Through a Pandemic Lens. Front Sustain Cities 2021;3:645914. [DOI: 10.3389/frsc.2021.645914] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
26 Damiani G, Gironi LC, Grada A, Kridin K, Finelli R, Buja A, Bragazzi NL, Pigatto PDM, Savoia P. COVID-19 related masks increase severity of both acne (maskne) and rosacea (mask rosacea): Multi-center, real-life, telemedical, and observational prospective study. Dermatol Ther 2021;34:e14848. [PMID: 33533563 DOI: 10.1111/dth.14848] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 7.0] [Reference Citation Analysis]
27 Mao Z, Zou Q, Yao H, Wu J. The application framework of big data technology in the COVID-19 epidemic emergency management in local government-a case study of Hainan Province, China. BMC Public Health 2021;21:2001. [PMID: 34736445 DOI: 10.1186/s12889-021-12065-0] [Reference Citation Analysis]
28 Wang Y. Intelligent Simulation of Children's Psychological Path Selection Based on Chaotic Neural Network Algorithm. Comput Intell Neurosci 2021;2021:5321153. [PMID: 34630545 DOI: 10.1155/2021/5321153] [Reference Citation Analysis]
29 Mao Z, Yao H, Zou Q, Zhang W, Dong Y. Digital Contact Tracing Based on a Graph Database Algorithm for Emergency Management During the COVID-19 Epidemic: Case Study. JMIR Mhealth Uhealth 2021;9:e26836. [PMID: 33460389 DOI: 10.2196/26836] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
30 Mushi A, Yassin Y, Khan A, Yezli S, Almuzaini Y. Knowledge, Attitude, and Perceived Risks Towards COVID-19 Pandemic and the Impact of Risk Communication Messages on Healthcare Workers in Saudi Arabia. Risk Manag Healthc Policy 2021;14:2811-24. [PMID: 34262368 DOI: 10.2147/RMHP.S306402] [Reference Citation Analysis]
31 Subramanian M, Shanmuga Vadivel K, Hatamleh WA, Alnuaim AA, Abdelhady M, V E S. The role of contemporary digital tools and technologies in Covid-19 crisis: An exploratory analysis. Expert Syst 2021. [PMID: 34898797 DOI: 10.1111/exsy.12834] [Reference Citation Analysis]
32 Vekaria D, Kumari A, Tanwar S, Kumar N. ξboost: An AI-Based Data Analytics Scheme for COVID-19 Prediction and Economy Boosting. IEEE Internet Things J 2021;8:15977-89. [PMID: 35582241 DOI: 10.1109/JIOT.2020.3047539] [Cited by in Crossref: 6] [Cited by in F6Publishing: 2] [Article Influence: 6.0] [Reference Citation Analysis]
33 Kakderi C, Oikonomaki E, Papadaki I. Smart and Resilient Urban Futures for Sustainability in the Post COVID-19 Era: A Review of Policy Responses on Urban Mobility. Sustainability 2021;13:6486. [DOI: 10.3390/su13116486] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 5.0] [Reference Citation Analysis]
34 Demertzis K, Taketzis D, Tsiotas D, Magafas L, Iliadis L, Kikiras P. Pandemic Analytics by Advanced Machine Learning for Improved Decision Making of COVID-19 Crisis. Processes 2021;9:1267. [DOI: 10.3390/pr9081267] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
35 Di Franco S, Alfieri A, Petrou S, Damiani G, Passavanti MB, Pace MC, Leone S, Fiore M. Current status of COVID-19 treatment: An opinion review. World J Virol 2020; 9(3): 27-37 [PMID: 33024717 DOI: 10.5501/wjv.v9.i3.27] [Cited by in CrossRef: 6] [Cited by in F6Publishing: 5] [Article Influence: 3.0] [Reference Citation Analysis]
36 Tayara H, Abdelbaky I, To Chong K. Recent omics-based computational methods for COVID-19 drug discovery and repurposing. Brief Bioinform 2021;22:bbab339. [PMID: 34423353 DOI: 10.1093/bib/bbab339] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
37 Zhou Y, Feng L, Zhang X, Wang Y, Wang S, Wu T. Spatiotemporal patterns of the COVID-19 control measures impact on industrial production in Wuhan using time-series earth observation data. Sustain Cities Soc 2021;75:103388. [PMID: 34608429 DOI: 10.1016/j.scs.2021.103388] [Reference Citation Analysis]
38 Jin Y, Li B, Gu Y. Analysis of Ice and Snow Path Planning System Based on MNN Algorithm. Computational Intelligence and Neuroscience 2022;2022:1-8. [DOI: 10.1155/2022/1586006] [Reference Citation Analysis]
39 Mohapatra B, Tripathy S, Singhal D, Saha R. Significance of digital technology in manufacturing sectors: Examination of key factors during Covid-19. Research in Transportation Economics 2021. [DOI: 10.1016/j.retrec.2021.101134] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
40 Eltoukhy AEE, Shaban IA, Chan FTS, Abdel-Aal MAM. Data Analytics for Predicting COVID-19 Cases in Top Affected Countries: Observations and Recommendations. Int J Environ Res Public Health 2020;17:E7080. [PMID: 32992643 DOI: 10.3390/ijerph17197080] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
41 Huang Z, Feng Z. Public Health and Private Life Under COVID-19 Vaccination Policies in China: A Legal Analysis. Risk Manag Healthc Policy 2021;14:4627-38. [PMID: 34849038 DOI: 10.2147/RMHP.S336434] [Reference Citation Analysis]
42 Haafza LA, Awan MJ, Abid A, Yasin A, Nobanee H, Farooq MS. Big Data COVID-19 Systematic Literature Review: Pandemic Crisis. Electronics 2021;10:3125. [DOI: 10.3390/electronics10243125] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 5.0] [Reference Citation Analysis]
43 Rachmawati R, Sari AD, Sukawan HAR, Widhyastana IMA, Ghiffari RA. The Use of ICT-Based Applications to Support the Implementation of Smart Cities during the COVID-19 Pandemic in Indonesia. Infrastructures 2021;6:119. [DOI: 10.3390/infrastructures6090119] [Cited by in Crossref: 3] [Article Influence: 3.0] [Reference Citation Analysis]
44 Wang Q, Su M, Zhang M, Li R. Integrating Digital Technologies and Public Health to Fight Covid-19 Pandemic: Key Technologies, Applications, Challenges and Outlook of Digital Healthcare. Int J Environ Res Public Health 2021;18:6053. [PMID: 34199831 DOI: 10.3390/ijerph18116053] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
45 El Samad M, El Nemar S, Sakka G, El-chaarani H. An innovative big data framework for exploring the impact on decision-making in the European Mediterranean healthcare sector. EMJB 2022. [DOI: 10.1108/emjb-11-2021-0168] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
46 Jiang L, Wu Z, Xu X, Zhan Y, Jin X, Wang L, Qiu Y. Opportunities and challenges of artificial intelligence in the medical field: current application, emerging problems, and problem-solving strategies. J Int Med Res 2021;49:3000605211000157. [PMID: 33771068 DOI: 10.1177/03000605211000157] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
47 Banerjee I, Robinson J, Kashyap A, Mohabeer P, Sathian B. COVID-19 and Artificial Intelligence: the pandemic pacifier. Nepal J Epidemiol 2020;10:919-22. [PMID: 33495709 DOI: 10.3126/nje.v10i4.33334] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
48 Montes-Orozco E, Mora-Gutierrez RA, De-Los-Cobos-Silva SG, Rincon-Garcia EA, Torres-Cockrell GS, Juarez-Gomez J, Obregon-Quintana B, Lara-Velazquez P, Gutierrez-Andrade MA. Identification of COVID-19 Spreaders Using Multiplex Networks Approach. IEEE Access 2020;8:122874-83. [PMID: 34192111 DOI: 10.1109/ACCESS.2020.3007726] [Cited by in Crossref: 5] [Article Influence: 2.5] [Reference Citation Analysis]
49 Kentikelenis AE, Seabrooke L. Governing and Measuring Health Security: The Global Push for Pandemic Preparedness Indicators. Global Policy. [DOI: 10.1111/1758-5899.13090] [Reference Citation Analysis]
50 Riswantini D, Nugraheni E, Arisal A, Khotimah PH, Munandar D, Suwarningsih W. Big Data Research in Fighting COVID-19: Contributions and Techniques. BDCC 2021;5:30. [DOI: 10.3390/bdcc5030030] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
51 Thomas LB, Mastorides SM, Viswanadhan NA, Jakey CE, Borkowski AA. Artificial Intelligence: Review of Current and Future Applications in Medicine. Fed Pract 2021;38:527-38. [PMID: 35136337 DOI: 10.12788/fp.0174] [Reference Citation Analysis]
52 Agbehadji IE, Awuzie BO, Ngowi AB, Millham RC. Review of Big Data Analytics, Artificial Intelligence and Nature-Inspired Computing Models towards Accurate Detection of COVID-19 Pandemic Cases and Contact Tracing. Int J Environ Res Public Health 2020;17:E5330. [PMID: 32722154 DOI: 10.3390/ijerph17155330] [Cited by in Crossref: 43] [Cited by in F6Publishing: 23] [Article Influence: 21.5] [Reference Citation Analysis]
53 Adadi A, Lahmer M, Nasiri S. Artificial Intelligence and COVID-19: A Systematic umbrella review and roads ahead. Journal of King Saud University - Computer and Information Sciences 2021. [DOI: 10.1016/j.jksuci.2021.07.010] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
54 Chang Z, Zhan Z, Zhao Z, You Z, Liu Y, Yan Z, Fu Y, Liang W, Zhao L. Application of artificial intelligence in COVID-19 medical area: a systematic review. J Thorac Dis 2021;13:7034-53. [PMID: 35070385 DOI: 10.21037/jtd-21-747] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
55 Nsaif MK, Mahdi BA, Bahar Al-mayouf YR, Mahdi OA, Aljaaf AJ, Khan S. An online COVID-19 self-assessment framework supported by IoMT technology. Journal of Intelligent Systems 2020;30:966-75. [DOI: 10.1515/jisys-2021-0048] [Reference Citation Analysis]
56 Tagde P, Tagde S, Bhattacharya T, Tagde P, Chopra H, Akter R, Kaushik D, Rahman MH. Blockchain and artificial intelligence technology in e-Health. Environ Sci Pollut Res Int 2021;28:52810-31. [PMID: 34476701 DOI: 10.1007/s11356-021-16223-0] [Reference Citation Analysis]
57 Chen X. Optimization of Data Mining and Analysis System for Chinese Language Teaching Based on Convolutional Neural Network. Comput Intell Neurosci 2021;2021:1148954. [PMID: 34899886 DOI: 10.1155/2021/1148954] [Reference Citation Analysis]
58 Chitcharoen S, Sivapornnukul P, Payungporn S. Revolutionized virome research using systems microbiology approaches. Exp Biol Med (Maywood) 2022;:15353702221102895. [PMID: 35723062 DOI: 10.1177/15353702221102895] [Reference Citation Analysis]
59 Lai C, Yu R, Wang M, Xian W, Zhao X, Tang Q, Chen R, Zhou X, Li X, Li Z, Li Z, Deng G, Wang F. Shorter incubation period is associated with severe disease progression in patients with COVID-19. Virulence 2020;11:1443-52. [PMID: 33108255 DOI: 10.1080/21505594.2020.1836894] [Cited by in Crossref: 5] [Cited by in F6Publishing: 6] [Article Influence: 2.5] [Reference Citation Analysis]
60 Kostkova P, Saigí-Rubió F, Eguia H, Borbolla D, Verschuuren M, Hamilton C, Azzopardi-Muscat N, Novillo-Ortiz D. Data and Digital Solutions to Support Surveillance Strategies in the Context of the COVID-19 Pandemic. Front Digit Health 2021;3:707902. [PMID: 34713179 DOI: 10.3389/fdgth.2021.707902] [Reference Citation Analysis]
61 Özgüven YM, Eken S. Distributed messaging and light streaming system for combating pandemics: A case study on spatial analysis of COVID-19 Geo-tagged Twitter dataset. J Ambient Intell Humaniz Comput 2021;:1-15. [PMID: 34127932 DOI: 10.1007/s12652-021-03328-0] [Reference Citation Analysis]
62 Yi J, Zhang H, Mao J, Chen Y, Zhong H, Wang Y. Review on the COVID-19 pandemic prevention and control system based on AI. Eng Appl Artif Intell 2022;114:105184. [PMID: 35846728 DOI: 10.1016/j.engappai.2022.105184] [Reference Citation Analysis]
63 Väänänen A, Haataja K, Vehviläinen-Julkunen K, Toivanen P. Proposal of a novel Artificial Intelligence Distribution Service platform for healthcare. F1000Res 2021;10:245. [PMID: 34804493 DOI: 10.12688/f1000research.36775.1] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
64 Zhang L, Darzi A, Ghader S, Pack ML, Xiong C, Yang M, Sun Q, Kabiri A, Hu S. Interactive COVID-19 Mobility Impact and Social Distancing Analysis Platform. Transportation Research Record. [DOI: 10.1177/03611981211043813] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
65 Schintler LA, Mcneely CL. Artificial intelligence, institutions, and resilience: Prospects and provocations for cities. Journal of Urban Management 2022;11:256-68. [DOI: 10.1016/j.jum.2022.05.004] [Reference Citation Analysis]
66 Sarría-Santamera A, Yeskendir A, Maulenkul T, Orazumbekova B, Gaipov A, Imaz-Iglesia I, Pinilla-Navas L, Moreno-Casbas T, Corral T. Population Health and Health Services: Old Challenges and New Realities in the COVID-19 Era. Int J Environ Res Public Health 2021;18:1658. [PMID: 33572355 DOI: 10.3390/ijerph18041658] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
67 Behzadifar M, Imani-Nasab MH, Martini M, Ghanbari MK, Bakhtiari A, Bragazzi NL. Universal Health Coverage to counteract the economic impact of the COVID-19 infection: current practices and ethical challenges. J Prev Med Hyg 2020;61:E520-4. [PMID: 33628955 DOI: 10.15167/2421-4248/jpmh2020.61.4.1581] [Reference Citation Analysis]
68 Papagiannidis S, Davlembayeva D. Bringing Smart Home Technology to Peer-to-Peer Accommodation: Exploring the Drivers of Intention to Stay in Smart Accommodation. Inf Syst Front 2021;:1-20. [PMID: 34899040 DOI: 10.1007/s10796-021-10227-4] [Reference Citation Analysis]
69 Minghini M, Sarretta A, Napolitano M. OpenStreetMap Contribution to Local Data Ecosystems in COVID-19 Times: Experiences and Reflections from the Italian Case. Data 2022;7:39. [DOI: 10.3390/data7040039] [Reference Citation Analysis]
70 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] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
71 Cury RC, Megyeri I, Lindsey T, Macedo R, Batlle J, Kim S, Baker B, Harris R, Clark RH. Natural Language Processing and Machine Learning for Detection of Respiratory Illness by Chest CT Imaging and Tracking of COVID-19 Pandemic in the US. Radiol Cardiothorac Imaging 2021;3:e200596. [PMID: 33778666 DOI: 10.1148/ryct.2021200596] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
72 Kampa P, Balzer F. Algorithmic literacy in medical students - results of a knowledge test conducted in Germany. Health Info Libr J 2021;38:224-30. [PMID: 34549514 DOI: 10.1111/hir.12392] [Reference Citation Analysis]
73 Li S, Ansari IS. Promotion and Influence of Big Data and Artificial Intelligence in Field of Drama and Film. Mobile Information Systems 2022;2022:1-10. [DOI: 10.1155/2022/5986283] [Reference Citation Analysis]
74 Pradana AR, Madjid SR, Prayitno HJ, Utami RD, Dharmawan Y. Potential Applications of Big Data for Managing the COVID-19 Pandemic. J Phys : Conf Ser 2021;1720:012002. [DOI: 10.1088/1742-6596/1720/1/012002] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
75 Guo Y, Zhang Y, Lyu T, Prosperi M, Wang F, Xu H, Bian J. The application of artificial intelligence and data integration in COVID-19 studies: a scoping review. J Am Med Inform Assoc 2021;28:2050-67. [PMID: 34151987 DOI: 10.1093/jamia/ocab098] [Reference Citation Analysis]
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