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For: Wong ZSY, Zhou J, Zhang Q. Artificial Intelligence for infectious disease Big Data Analytics. Infect Dis Health 2019;24:44-8. [PMID: 30541697 DOI: 10.1016/j.idh.2018.10.002] [Cited by in Crossref: 69] [Cited by in F6Publishing: 33] [Article Influence: 17.3] [Reference Citation Analysis]
Number Citing Articles
1 Ng YL, Salim CK, Chu JJH. Drug repurposing for COVID-19: Approaches, challenges and promising candidates. Pharmacol Ther 2021;228:107930. [PMID: 34174275 DOI: 10.1016/j.pharmthera.2021.107930] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Wirtz BW, Langer PF, Fenner C. Artificial Intelligence in the Public Sector - a Research Agenda. International Journal of Public Administration 2021;44:1103-28. [DOI: 10.1080/01900692.2021.1947319] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
3 [DOI: 10.1109/ithings-greencom-cpscom-smartdata-cybermatics53846.2021.00067] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Kolak M, Li X, Lin Q, Wang R, Menghaney M, Yang S, Anguiano V Jr. The US COVID Atlas: A dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic. Trans GIS 2021;25:1741-65. [PMID: 34512108 DOI: 10.1111/tgis.12786] [Reference Citation Analysis]
5 Marzouk M, Elshaboury N, Abdel-Latif A, Azab S. Deep learning model for forecasting COVID-19 outbreak in Egypt. Process Saf Environ Prot 2021;153:363-75. [PMID: 34334966 DOI: 10.1016/j.psep.2021.07.034] [Reference Citation Analysis]
6 Car Z, Baressi Šegota S, Anđelić N, Lorencin I, Mrzljak V. Modeling the Spread of COVID-19 Infection Using a Multilayer Perceptron. Comput Math Methods Med 2020;2020:5714714. [PMID: 32565882 DOI: 10.1155/2020/5714714] [Cited by in Crossref: 42] [Cited by in F6Publishing: 18] [Article Influence: 21.0] [Reference Citation Analysis]
7 Vandenberg O, Durand G, Hallin M, Diefenbach A, Gant V, Murray P, Kozlakidis Z, van Belkum A. Consolidation of Clinical Microbiology Laboratories and Introduction of Transformative Technologies. Clin Microbiol Rev 2020;33:e00057-19. [PMID: 32102900 DOI: 10.1128/CMR.00057-19] [Cited by in Crossref: 14] [Cited by in F6Publishing: 7] [Article Influence: 7.0] [Reference Citation Analysis]
8 Rajan RS, Kumar KJ, Shantrinal AA, Rajalaxmi TM, Rajasingh I, Balasubramanian K. Biochemical and phylogenetic networks-I: hypertrees and corona products. J Math Chem 2021;:1-23. [PMID: 33583991 DOI: 10.1007/s10910-020-01194-3] [Cited by in Crossref: 3] [Article Influence: 3.0] [Reference Citation Analysis]
9 Ouyang L, Yuan Y, Cao Y, Wang FY. A novel framework of collaborative early warning for COVID-19 based on blockchain and smart contracts. Inf Sci (N Y) 2021;570:124-43. [PMID: 33846657 DOI: 10.1016/j.ins.2021.04.021] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
10 Alfred R, Obit JH. The roles of machine learning methods in limiting the spread of deadly diseases: A systematic review. Heliyon 2021;7:e07371. [PMID: 34179541 DOI: 10.1016/j.heliyon.2021.e07371] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
11 Malik YS, Sircar S, Bhat S, Ansari MI, Pande T, Kumar P, Mathapati B, Balasubramanian G, Kaushik R, Natesan S, Ezzikouri S, El Zowalaty ME, Dhama K. How artificial intelligence may help the Covid-19 pandemic: Pitfalls and lessons for the future. Rev Med Virol 2020;:e2205. [PMID: 33476063 DOI: 10.1002/rmv.2205] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
12 Simsek M, Kantarci B. Artificial Intelligence-Empowered Mobilization of Assessments in COVID-19-like Pandemics: A Case Study for Early Flattening of the Curve. Int J Environ Res Public Health 2020;17:E3437. [PMID: 32423150 DOI: 10.3390/ijerph17103437] [Cited by in Crossref: 19] [Cited by in F6Publishing: 7] [Article Influence: 9.5] [Reference Citation Analysis]
13 Li L, Novillo-Ortiz D, Azzopardi-Muscat N, Kostkova P. Digital Data Sources and Their Impact on People's Health: A Systematic Review of Systematic Reviews. Front Public Health 2021;9:645260. [PMID: 34026711 DOI: 10.3389/fpubh.2021.645260] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
14 Mir UB, Sharma S, Kar AK, Gupta MP. Critical success factors for integrating artificial intelligence and robotics. DPRG 2020;22:307-31. [DOI: 10.1108/dprg-03-2020-0032] [Cited by in Crossref: 16] [Cited by in F6Publishing: 9] [Article Influence: 8.0] [Reference Citation Analysis]
15 Ngabo D, Dong W, Ibeke E, Iwendi C, Masabo E. Tackling pandemics in smart cities using machine learning architecture. Math Biosci Eng 2021;18:8444-61. [PMID: 34814307 DOI: 10.3934/mbe.2021418] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 5.0] [Reference Citation Analysis]
16 Cui M. Big data medical behavior analysis based on machine learning and wireless sensors. Neural Comput & Applic 2022;34:9413-27. [DOI: 10.1007/s00521-021-06369-w] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
17 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]
18 Bongomin O, Gilibrays Ocen G, Oyondi Nganyi E, Musinguzi A, Omara T. Exponential Disruptive Technologies and the Required Skills of Industry 4.0. Journal of Engineering 2020;2020:1-17. [DOI: 10.1155/2020/4280156] [Cited by in Crossref: 24] [Cited by in F6Publishing: 2] [Article Influence: 12.0] [Reference Citation Analysis]
19 Zhang Q, Gao J, Wu JT, Cao Z, Dajun Zeng D. Data science approaches to confronting the COVID-19 pandemic: a narrative review. Philos Trans A Math Phys Eng Sci 2022;380:20210127. [PMID: 34802267 DOI: 10.1098/rsta.2021.0127] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
20 Liu N, Chee ML, Niu C, Pek PP, Siddiqui FJ, Ansah JP, Matchar DB, Lam SSW, Abdullah HR, Chan A, Malhotra R, Graves N, Koh MS, Yoon S, Ho AFW, Ting DSW, Low JGH, Ong MEH. Coronavirus disease 2019 (COVID-19): an evidence map of medical literature. BMC Med Res Methodol 2020;20:177. [PMID: 32615936 DOI: 10.1186/s12874-020-01059-y] [Cited by in Crossref: 31] [Cited by in F6Publishing: 22] [Article Influence: 15.5] [Reference Citation Analysis]
21 Simsek M, Boukerche A, Kantarci B, Khan S. AI-driven autonomous vehicles as COVID-19 assessment centers: A novel crowdsensing-enabled strategy. Pervasive and Mobile Computing 2021;75:101426. [DOI: 10.1016/j.pmcj.2021.101426] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
22 Hussain A, Malik H, Chaudhry MU. Supervised Learning Based Classification of Cardiovascular Diseases. Proc eng technol innov 2021;20:24-34. [DOI: 10.46604/peti.2021.7217] [Reference Citation Analysis]
23 Al-Ruzzieh MA, Ayaad O, Qaddumi B. The role of e-health in improving control and management of COVID 19 outbreak: current perspectives. Int J Adolesc Med Health 2020:/j/ijamh. [PMID: 32866117 DOI: 10.1515/ijamh-2020-0072] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
24 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]
25 Costa DG, Peixoto JPJ. COVID‐19 pandemic: a review of smart cities initiatives to face new outbreaks. IET Smart Cities 2020;2:64-73. [DOI: 10.1049/iet-smc.2020.0044] [Cited by in Crossref: 27] [Cited by in F6Publishing: 2] [Article Influence: 13.5] [Reference Citation Analysis]
26 Yousefinaghani S, Dara RA, Poljak Z, Sharif S. A decision support framework for prediction of avian influenza. Sci Rep 2020;10:19011. [PMID: 33149144 DOI: 10.1038/s41598-020-75889-7] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
27 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]
28 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]
29 Allam Z, Dey G, Jones D. Artificial Intelligence (AI) Provided Early Detection of the Coronavirus (COVID-19) in China and Will Influence Future Urban Health Policy Internationally. AI 2020;1:156-65. [DOI: 10.3390/ai1020009] [Cited by in Crossref: 49] [Cited by in F6Publishing: 2] [Article Influence: 24.5] [Reference Citation Analysis]
30 Zaman U, Imran, Mehmood F, Iqbal N, Kim J, Ibrahim M. Towards Secure and Intelligent Internet of Health Things: A Survey of Enabling Technologies and Applications. Electronics 2022;11:1893. [DOI: 10.3390/electronics11121893] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
31 Li Y, Lv Z. Intelligent Environmental Art Design Combining Big Data and Artificial Intelligence. Complexity 2021;2021:1-11. [DOI: 10.1155/2021/1606262] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
32 Ghafouri-Fard S, Mohammad-Rahimi H, Motie P, Minabi MAS, Taheri M, Nateghinia S. Application of machine learning in the prediction of COVID-19 daily new cases: A scoping review. Heliyon 2021;7:e08143. [PMID: 34660935 DOI: 10.1016/j.heliyon.2021.e08143] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
33 Cartelle Gestal M, Dedloff MR, Torres-sangiao E. Computational Health Engineering Applied to Model Infectious Diseases and Antimicrobial Resistance Spread. Applied Sciences 2019;9:2486. [DOI: 10.3390/app9122486] [Cited by in Crossref: 9] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
34 Winkler DA. Use of Artificial Intelligence and Machine Learning for Discovery of Drugs for Neglected Tropical Diseases. Front Chem 2021;9:614073. [PMID: 33791277 DOI: 10.3389/fchem.2021.614073] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
35 Degeling C, Carter SM, van Oijen AM, McAnulty J, Sintchenko V, Braunack-Mayer A, Yarwood T, Johnson J, Gilbert GL. Community perspectives on the benefits and risks of technologically enhanced communicable disease surveillance systems: a report on four community juries. BMC Med Ethics 2020;21:31. [PMID: 32334597 DOI: 10.1186/s12910-020-00474-6] [Cited by in Crossref: 5] [Cited by in F6Publishing: 7] [Article Influence: 2.5] [Reference Citation Analysis]
36 Edo-Osagie O, Smith G, Lake I, Edeghere O, De La Iglesia B. Twitter mining using semi-supervised classification for relevance filtering in syndromic surveillance. PLoS One 2019;14:e0210689. [PMID: 31318885 DOI: 10.1371/journal.pone.0210689] [Cited by in Crossref: 12] [Cited by in F6Publishing: 7] [Article Influence: 4.0] [Reference Citation Analysis]
37 El-Haddadeh R, Fadlalla A, Hindi NM. Is There a Place for Responsible Artificial Intelligence in Pandemics? A Tale of Two Countries. Inf Syst Front 2021;:1-17. [PMID: 33972823 DOI: 10.1007/s10796-021-10140-w] [Reference Citation Analysis]
38 Shen YT, Chen L, Yue WW, Xu HX. Digital Technology-Based Telemedicine for the COVID-19 Pandemic. Front Med (Lausanne) 2021;8:646506. [PMID: 34295908 DOI: 10.3389/fmed.2021.646506] [Reference Citation Analysis]
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40 Brownson RC, Burke TA, Colditz GA, Samet JM. Reimagining Public Health in the Aftermath of a Pandemic. Am J Public Health 2020;110:1605-10. [PMID: 32816552 DOI: 10.2105/AJPH.2020.305861] [Cited by in Crossref: 14] [Cited by in F6Publishing: 8] [Article Influence: 7.0] [Reference Citation Analysis]
41 Guo H, Nativi S, Liang D, Craglia M, Wang L, Schade S, Corban C, He G, Pesaresi M, Li J, Shirazi Z, Liu J, Annoni A. Big Earth Data science: an information framework for a sustainable planet. International Journal of Digital Earth 2020;13:743-67. [DOI: 10.1080/17538947.2020.1743785] [Cited by in Crossref: 25] [Cited by in F6Publishing: 3] [Article Influence: 12.5] [Reference Citation Analysis]
42 Dogan O, Tiwari S, Jabbar MA, Guggari S. A systematic review on AI/ML approaches against COVID-19 outbreak. Complex Intell Systems 2021;:1-24. [PMID: 34777970 DOI: 10.1007/s40747-021-00424-8] [Cited by in Crossref: 3] [Article Influence: 3.0] [Reference Citation Analysis]
43 Mazzoleni S, Turchetti G, Ambrosino N. The COVID-19 outbreak: From "black swan" to global challenges and opportunities. Pulmonology 2020;26:117-8. [PMID: 32291202 DOI: 10.1016/j.pulmoe.2020.03.002] [Cited by in Crossref: 23] [Cited by in F6Publishing: 13] [Article Influence: 11.5] [Reference Citation Analysis]
44 Shanbehzadeh M, Kazemi-Arpanahi H, Orooji A, Mobarak S, Jelvay S. Performance evaluation of selected machine learning algorithms for COVID-19 prediction using routine clinical data: With versus Without CT scan features. J Educ Health Promot 2021;10:285. [PMID: 34667785 DOI: 10.4103/jehp.jehp_1424_20] [Reference Citation Analysis]
45 Zhang G, Liu X. Prediction and control of COVID-19 spreading based on a hybrid intelligent model. PLoS One 2021;16:e0246360. [PMID: 33571234 DOI: 10.1371/journal.pone.0246360] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
46 Odone A, Buttigieg S, Ricciardi W, Azzopardi-Muscat N, Staines A. Public health digitalization in Europe. Eur J Public Health 2019;29:28-35. [PMID: 31738441 DOI: 10.1093/eurpub/ckz161] [Cited by in Crossref: 15] [Cited by in F6Publishing: 9] [Article Influence: 7.5] [Reference Citation Analysis]
47 Elsotouhy M, Jain G, Shrivastava A. Disaster Management during Pandemic: A Big Data-Centric Approach. Int J Innovation Technol Management 2021;18:2140003. [DOI: 10.1142/s0219877021400034] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
48 Djenouri Y, Srivastava G, Yazidi A, Lin JC. An edge-driven multi-agent optimization model for infectious disease detection. Appl Intell. [DOI: 10.1007/s10489-021-03145-0] [Reference Citation Analysis]
49 Rashid MA, Ahmad S, Siddiqui MK, Manzoor S, Dhlamini M, Pradeep S. An Analysis of Eccentricity-Based Invariants for Biochemical Hypernetworks. Complexity 2021;2021:1-14. [DOI: 10.1155/2021/1974642] [Reference Citation Analysis]
50 Kaur I, Behl T, Aleya L, Rahman H, Kumar A, Arora S, Bulbul IJ. Artificial intelligence as a fundamental tool in management of infectious diseases and its current implementation in COVID-19 pandemic. Environ Sci Pollut Res Int 2021;28:40515-32. [PMID: 34036497 DOI: 10.1007/s11356-021-13823-8] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
51 Bernardo T, Sobkowich KE, Forrest RO, Stewart LS, D'Agostino M, Perez Gutierrez E, Gillis D. Collaborating in the Time of COVID-19: The Scope and Scale of Innovative Responses to a Global Pandemic. JMIR Public Health Surveill 2021;7:e25935. [PMID: 33503001 DOI: 10.2196/25935] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
52 Leng J, Wang D, Ma X, Yu P, Wei L, Chen W. Bi-level artificial intelligence model for risk classification of acute respiratory diseases based on Chinese clinical data. Appl Intell. [DOI: 10.1007/s10489-022-03222-y] [Reference Citation Analysis]
53 Khan SM, Liu X, Nath S, Korot E, Faes L, Wagner SK, Keane PA, Sebire NJ, Burton MJ, Denniston AK. A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability. Lancet Digit Health 2021;3:e51-66. [PMID: 33735069 DOI: 10.1016/S2589-7500(20)30240-5] [Cited by in Crossref: 13] [Cited by in F6Publishing: 3] [Article Influence: 6.5] [Reference Citation Analysis]
54 Anđelić N, Baressi Šegota S, Lorencin I, Mrzljak V, Car Z. Estimation of COVID-19 epidemic curves using genetic programming algorithm. Health Informatics J 2021;27:1460458220976728. [PMID: 33459107 DOI: 10.1177/1460458220976728] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]