XR, AI, IoT, and 5G Applications in Fight Against the COVID-19 Pandemic

Abstract

To struggle the devastating impact of the Coronavirus disease pandemic, governments have had to implement containment and closure policies. While these practices caused the disruption of activities in many sectors, on the contrary, they led to an increase in demand for healthcare, making it necessary to operate above the capacity to make control of contagious. In this context, there has been an increase in the use of innovative technologies such as extended reality, artificial intelligence, internet of things, and 5G in order to effectively fight against the pandemic. In this review, it is aimed to reveal the fields of usage and model implementation of related innovative technologies during the pandemic process. These technologies have provided various benefits for health facilities, health workers, patients, and health systems, in many areas such as the delivery of health care for COVID-19, application of diagnosis and treatment methods, medical education, public health, and health promotion. These benefits can be summarized as improving customer service and quality, saving resources and providing competitive advantages for health facilities; protecting and promoting health, ensuring patient safety and cost savings for patients; providing a safe working environment for health care workers; providing effective capacity utilization and balance between supply and demand for healthcare, health care worker training, improving public health, propounding data reliability and traceability for healthcare systems. In crisis situations such as like a pandemics in healthcare processes, governments must inevitably use innovative technologies. In this context, it is important to consider these technologies while developing policies for both workforce training and existing infrastructure in healthcare.

Keywords

• COVID-19
• Artificial Intelligence
• Internet of Things
• virtual reality
• augmented reality.

COVID-19 Pandemisi ile Mücadelede XR, AI, IoT ve 5G Uygulamaları

Abstract

Koronavirüs hastalığı pandemisinin yıkıcı etkisiyle mücadelede hükümetler, sınırlama ve kapanma politikaları uygulamak durumunda kalmıştır. Bu uygulamalar pek çok sektörde faaliyetlerin aksamasına sebep olurken, sağlık hizmetleri sektöründe aksine talep artışına yol açarak bulaşıcılığın kontrolünü sağlayacak şekilde kapasite üzerinde faaliyet gösterilmesini gerekli kılmıştır. Bu kapsamda pandemi ile etkin bir şekilde mücadele edebilmek için genişletilmiş gerçeklik, yapay zekâ, nesnelerin interneti ve 5G gibi yenilikçi teknolojilerin kullanımında artış görülmüştür. Bu derlemede pandemi sürecinde ilgili yenilikçi teknolojilerin kullanım alanlarının ve örnek uygulamalarının ortaya konulması amaçlanmaktadır. Bu teknolojiler, COVID-19’a yönelik sağlık hizmetlerinin sunumu, teşhis ve tedavi yöntemlerinin uygulanması, tıp eğitimi, halk sağlığı ve sağlığın geliştirilmesi gibi pek çok alanda sağlık işletmeleri, sağlık çalışanları, hastalar ve bir bütün olarak sağlık sistemleri için çeşitli faydalar sağlamıştır. Bu faydalar sağlık işletmeleri için müşteri hizmetleri ve kalitenin geliştirilmesi, kaynak tasarrufu ve rekabet üstünlüğünün sağlanması; hastalar açısından sağlığın korunması ve geliştirilmesi, hasta güvenliğinin ve maliyet tasarrufunun sağlanması; sağlık çalışanları için daha güvenli bir çalışma ortamının sağlanması; sağlık sistemlerine ise etkin kapasite kullanımı, sağlık hizmetleri arz ve talep dengesinin sağlanması, sağlık insan gücü eğitimi, halk sağlığının geliştirilmesi, veri güvenilirliği ve izlenebilirliğinin sağlanması olarak özetlenebilir. Sağlık hizmeti süreçlerinde pandemi gibi kriz durumlarında hükümetlerin yenilikçi teknolojileri kaçınılmaz olarak kullanması gerekmektedir. Bu doğrultuda sağlık hizmetlerinde ortaya çıkan ihtiyaçları karşılayabilmek için bu teknolojilerin hem insan gücü yetiştirme hem de mevcut altyapıya yönelik politikaların geliştirilmesinde kullanımı önem arz etmektedir.

Keywords

• COVID-19
• Yapay Zekâ
• Nesnelerin İnterneti
• Sanal Gerçeklik
• Artırılmış Gerçeklik
• virtual reality
• augmented reality.

References

1. T.C. Sağlık Bakanlığı Halk Sağlığı Genel Müdürlüğü. COVID-19 (SARS-CoV-2 Enfeksiyonu) Genel Bilgiler, Epidemiyoloji ve Tanı. Ankara; 2020. Available from: https://covid19.saglik.gov.tr/Eklenti/39551/0/covid-19re hberigenelbilgilerepidemiyolojivetanipdf.pdf
2. WHO. COVID-19 Weekly Epidemiological Update Issue Edition 90. 2022 May 4 [cited 2022 May 10]. Available from: https://apps.who.int/ iris/bitstream/handle/10665/353976/nCoV-weekly-sitrep4May22-eng. pdf?sequence=1&isAllowed=y
3. Wibawanto W, Nugrahani R, Mustikawan A. Reconstructing Majapahit Kingdom in virtual reality. Bandung Creative Movement 2016 [Internet]. 2016 Nov [cited 2022 Apr 17]; 3(1):420-7. Available from: https:// openlibrarypublications.telkomuniversity.ac.id/index.php/bcm/article/ view/5835/5817
4. Mann S, Furness T, Yuan Y, Iorio J, Wang Z. All reality: virtual, augmented, mixed (x), mediated (x,y), and multimediated reality. ArXiv Preprint ArXiv [Internet]. 2018 Apr 20 [cited 2022 Apr 15]; arXiv:1804.08386v1. Available from: https://arxiv.org/pdf/1804.08386.pdf
5. Tepper OM, Rudy HL, Lefkowitz A, Weimer KA, Marks SM, Stern CS, et al. Mixed reality with holoLens: where virtual reality meets augmented reality in the operating room. Plast Reconstr Surg [Internet]. 2017 Nov [cited 2022 Apr];140(5):1066-70. Available from: https://pubmed.ncbi.nlm.nih.gov/29068946/ DOI: 10.1097/PRS.0000000000003802
6. Milgram P, Kishino F. A taxonomy of mixed reality visual displays. IEICE Trans Inf Syst [Internet]. 1994 Dec [cited 2022 Apr 18];77(12):1321-29. Available from: https://cs.gmu.edu/~zduric/cs499/Readings/r76JBo-Milgram_IEICE_1994.pdf
7. Suh A, Prophet J. The state of immersive technology research: a literature analysis. Comput Human Behav [Internet]. 2018 Sep [cited 2022 Apr]; 86:77-90. Available from: https://www.sciencedirect.com/science/article/abs/pii/S0747563218301857 DOI:10.1016/j.chb.2018.04.019.
8. ABI Research [Internet]. Therapy and Training Services have the highest opportunity in VR medical and healthcare segment; 2017 Oct 5 [cited 2022 Sep 12]. Available from: https://www.abiresearch.com/press/virtual-reality-medicine-and-healthcare-generate-u/

9. ABI Research [Internet]. How the Future Is Shaped in Healthcare; 2018 [cited 2022 Sep 12]. Available from: https://www.abiresearch.com/market-research/product/1032408-a-new-journey-in-healthcare-with-augmented/
10. Asadzadeh A, Samad-Soltani T, Rezaei-Hachesu P. Applications of virtual and augmented reality in infectious disease epidemics with a focus on the COVID-19 outbreak. Inform Med Unlocked [Internet]. 2021 Apr 27 [cited 2022 Apr];24(100579):1-8. Available from: https://pubmed.ncbi.nlm.nih.gov/33937503/ DOI: 10.1016/j.imu.2021.100579
11. Liu P, Lu L, Liu S, Xie M, Zhang J, Huo T, et al. Mixed reality assists the fight against COVID-19. Intell Med [Internet]. 2021 May [cited 2022 Apr];1(1):16-8, Available from: https://www.sciencedirect.com/science/article/pii/S2667102621000115 DOI:10.1016/j.imed.2021.05.002.
12. Işık T. Sağlık Bilişim Teknolojileri ve Yapay Zekâ. 4. Uluslararası Sağlıkta Bilişim ve Bilgi Güvenliği Kongresi, Sağlık Akademisyenleri Derneği [Internet]. 2019 [cited 2022 Apr];17-35. Available from: https://www.sbu.edu.tr/FileFolder/Dosyalar/xoFsAuL2/2021_3/4hcs2019bilimselkitapsikistirildi-f5021124.pdf
13. Özkan Y, Selçukcan Erol Ç. Psikiyatride Yapay Zekâ. İçinde: Bulut M, Dilmen N, Bora EG, Gezer M, Selçukcan Erol Ç, editörler. Sağlık Bilimlerinde Yapay Zekâ. İstanbul: Çağlayan Kitabevi ve Eğitim Çözümleri Ticaret A.Ş., 2019. (s. 73-85).
14. InfoWorld, Tynan D. [Internet]. What is machine learning? Software derived from data; 2017 [cited 2022 Apr 27]. Available from: https://www.infoworld.com/article/3215266/what-is-machine-learning-software-derived-from-data.html
15. LeCun Y, Bengio Y, Hinton G. Deep learning. Nature [Internet]. 2015 May [cited 2022 Apr 28]; 521(7553):436-44. Available from: https://pubmed.ncbi.nlm.nih.gov/26017442/ DOI: 10.1038/nature14539.
16. Gilliam J, Rimmington L, Dance H, Verveij G, Rao A, Roberts KB, et al. Macroeconomic impact of artificial intelligence. PwC [Internet]. 2018 Feb [cited 2022 Sep]. Available from: https://www.pwc.co.uk/economic-services/assets/macroeconomic-impact-of-ai-technical-report-feb-18.pdf
17. Bora P [Internet]. 27 Companies Changing Health Outcomes Through AI. Digital Authority Partners; 2021 Sep 26 [cited 2022 Sep 13]. Available from: https://www.digitalauthority.me/resources/artificial-intelligence-in-healthcare/
18. Korte A, Tiberius V, Brem A. Internet of Things (IoT) Technology research in business and management literature: results from a co-citation analysis. J. Theor. Appl. Electron. Commer. Res [Internet]. 2021 Aug 17 [cited 2022 Apr 28]; 16(6):2073–2090. Available from: https://www.mdpi.com/0718-1876/16/6/116#cite DOI:10.3390/jtaer16060116.
19. Pradhan B, Bhattacharyya S, Pal K. IoT-Based applications in healthcare devices. J Healthc Eng [Internet]. 2021 Mar 19 [cited 2022 Apr 29]; 2021, Article ID: 6632599: 1-18. Available from: https://www.hindawi.com/journals/jhe/2021/6632599/ DOI:10.1155/2021/6632599.
20. Udoh IS, Kotonya G. Developing IoT applications: challenges and frameworks. IET Cyber-Physical Systems Theory & Applications [Internet]. 2018 Mar 17 [cited 2022 Apr 27];3(2):65-72. Available from: https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-cps.2017.0068 DOI:10.1049/iet-cps.2017.0068.
21. Islam SMR, Kwak D, Kabir MDH, Hossain M, Kwak KS. The Internet of Things for health care: a comprehensive survey. IEEE Access [Internet]. 2015 June 1 [cited 2022 Apr 16];3:678-708. Available from: https://ieeexplore.ieee.org/document/7113786/authors#authors DOI: 10.1109/ACCESS.2015.2437951
22. Javaid M, Khan IH. Internet of Things (IoT) enabled healthcare helps to take the challenges of COVID-19 Pandemic. J Oral Biol Craniofac Res [Internet]. 2021 Jan 30 [cited 2022 Apr 14]; 11(2):209-14. Available from: https://pubmed.ncbi.nlm.nih.gov/33665069/ DOI: 10.1016/j.jobcr.2021.01.015.
23. Nasajpour M, Pouriyeh S, Parizi RM, Dorodchi M, Valero M, Arabnia HR. Internet of Things for current COVID-19 and Future Pandemics: an exploratory study. J Healthc Inform Res [Internet]. 2020 Nov 12 [cited 2022 Apr 10];4(4):325-64. Available from: https://pubmed.ncbi.nlm.nih.gov/33204938/ DOI: 10.1007/s41666-020-00080-6.
24. Singh RP, Javaid M, Haleem A, Suman R. Internet of things (IoT) applications to fight against COVID-19 pandemic. Diabetes Metab Syndr [Internet]. 2020 Jul-Aug [cited 2022 Apr];14(4):521-24. Available from: https://pubmed.ncbi.nlm.nih.gov/32388333/ DOI: 10.1016/j.dsx.2020.04.041.
25. eMarketer [Internet]. US Adult Wearable Users and Penetration, 2017-2022 (millions and % of population). Insider Intelligence; 2018 Nov [cited 2022 Sep 13]. Available from:https://www.insiderintelligence.com/chart/224897/us-adult-wearable-users-penetration-2017-2022-millions-of-population
26. Fortune Business Insights [Internet]. Market Research Report. 2021 Oct [cited 2022 Sep 13] Available from: https://www.fortunebusinessinsights.com/industry-reports/internet-of-medical-things-iomt-market-101844
27. Mukhopadhyay A [Internet]. COVID-19 Impact on India Healthcare IT Market. Onometra; n.d. [cited 2022 Sep 13] Available from: https://onometra.com/covid-19-impact-on-india-healthcare-it-market/
28. McKinsey&Company [Internet]. The Internet of Things: Mapping the Value Beyond The Hype. 2015 June [cited 2022 Sep 13] Available from: https://www.mckinsey.com/~/media/McKinsey/Industries/Technology%20Media%20and%20Telecommunications/High%20Tech/Our%20Insights/The%20Internet%20of%20Things%20The%20value%20of%20digitizing%20the%20physical%20world/The-Internet-of-things-Mapping-the-value-beyond-the-hype.ashx
29. Lee LH, Braud T, Zhou P, Wang L, Xu D, Lin Z, et al. All one needs to know about metaverse: a complete survey on technological singularity, virtual ecosystem, and research agenda. Journal of Latex Class Files [Internet]. 2021 Oct [cited 2022 Apr];14(8):1–66. Available from: https://www.researchgate.net/publication/355172308_All_One_Needs_to_Know_about_Metaverse_A_Complete_Survey_on_Technological_Singularity_Virtual_Ecosystem_and_Research_
30. Muhammad G, Alqahtani S, Alelaiwi A. Pandemic management for diseases similar to COVID-19 using deep learning and 5G communications. IEEE Netw [Internet]. 2021 June [cited 2022 Apr];35(3):21-6. Available from: https://ieeexplore.ieee.org/document/9454580 DOI:10.1109/mnet.011.2000739.
31. Abubakar AI, Omeke KG, Ozturk M, Hussain S, Imran MA. The role of artificial intelligence driven 5G networks in COVID-19 outbreak: opportunities, challenges, and future outlook. Front Comms Net [Internet]. 2020 Nov 11 [cited 2022 Apr 9]; 1, Article 575065: 1-22. Available from: https://www.frontiersin.org/articles/10.3389/frcmn.2020.575065/full DOI:10.3389/frcmn.2020.575065
32. Chamola V, Hassija V, Gupta V, Guizani M. A comprehensive review of the COVID-19 pandemic and the role of IoT, drones, AI, blockchain, and 5G in managing its impact. IEEE Access [Internet]. 2020 May 4 [cited 2022 Apr 14];8: 90225-65. Available from: https://ieeexplore.ieee.org/document/9086010 DOI:10.1109/access.2020.2992341
33. Siddique L, Qadir J, Farooq S, Imran MA. How 5G (and concomitant technologies) will revolutionize healthcare. ArXiv Preprint ArXiv [Internet]. 2017 Aug 17 [cited 2022 Apr 16]; arXiv: 1708.08746. Available from: https://arxiv.org/abs/1708.08746 DOI:10.48550/ARXIV.1708.08746.
34. Grand View Research [Internet]. 5G Services Market Size & Share Report 2022-2030. Next Generation Technologies; 2022 [cited 2022 Sep 13]. Available from: https://www.grandviewresearch.com/industry-analysis/5g-services-market#
35. Ericsson [Internet]. Ericsson Mobility Report; 2022 June [cited 2022 Sep 30]. Available from:https://www.ericsson.com/49d3a0/assets/local/reports-papers/mobility-report/documents/2022/ericsson-mobility-report-june-2022.pdf.
36. GSA-(Global mobile Suppliers Association) [Internet]. 5G Market Snapshot; 2022 June [cited 2022 Sep 10]. Available from: https://gsacom.com/paper/5g-market-snapshot-june-2022/.
37. Markets and Markets [Internet]. 5G in Healthcare Market. 2021 [cited 2022 Sep 1]. Available from: https://www.marketsandmarkets.com/Market-Reports/5g-healthcare-market-248695375.html
38. Martin G, Koizia L, Kooner A, Cafferkey J, Ross C, Purkayastha S, et al. Use of the HoloLens2 mixed reality headset for protecting health care workers during the COVID-19 pandemic: prospective, observational evaluation. J Med Internet Res [Internet]. 2020 Aug 14 [cited 2022 Apr 22];22(8):e21486. Available from: https://www.jmir.org/2020/8/e21486/PDF DOI:10.2196/21486.
39. Ong T, Wilczewski H, Paige SR, Soni H, Welch BM, Bunnell BE. Extended reality for enhanced telehealth during and beyond COVID-19: viewpoint. JMIR Serious Games [Internet]. 2021 Jul 26 [cited 2022 Apr 23];9(3):e26520. Available from: https://pubmed.ncbi.nlm.nih.gov/34227992/ DOI: 10.2196/26520
40. Riva G, Mantovani F, Wiederhold BK. Positive technology and COVID-19. Cyberpsychol Behav Soc Netw [Internet]. 2020 Sep [cited 2022 Apr 17];23(9):581-587. Available from: https://pubmed.ncbi.nlm.nih.gov/32833511/ DOI: 10.1089/cyber.2020.29194.gri.
41. MIND-VR. [Internet]. What is MIND-VR? Who we are? MIND-VR; 2022 [cited 2022 May 08]. Available from: https://mind-vr.com/73-2/chi-siamo/
42. Wang SSY, Teo WZW, Teo WZY, Chai YW. Virtual reality as a bridge in palliative care during COVID-19. J Palliat Med [Internet]. 2020 June [cited 2022 Apr 18];23(6):756. Available from: https://pubmed.ncbi.nlm.nih.gov/32324080/ DOI: 10.1089/jpm.2020.0212.
43. Tamplin J, Loveridge B, Clarke K, Li Y, J Berlowitz D. Development and feasibility testing of an online virtual reality platform for delivering therapeutic group singing interventions for people living with spinal cord injury. J Telemed Telecare [Internet]. 2020 Jul [cited 2022 Apr 30];26(6):365-375. Available from: https://pubmed.ncbi.nlm.nih.gov/30823854/ DOI: 10.1177/1357633X19828463
44. Singh RP, Javaid M, Kataria R, Tyagi M, Haleem A, Suman R. Significant applications of virtual reality for COVID-19 pandemic. Diabetes Metab Syndr [Internet]. 2020 May 12 [cited 2022 Apr 19];14(4):661-664. Available from: https://pubmed.ncbi.nlm.nih.gov/32438329/ DOI: 10.1016/j.dsx.2020.05.011
45. Cox Sarah [Internet]. Visualising COVID-19 with VR. Goldsmiths University of London; 2017 [cited 2022 May 08]. Available from: https://www.gold.ac.uk/news/visualising-COVID-19-with-vr/
46. Couperus K, Young S, Walsh R, Kang C, Skinner C, Essendrop R, et al. Immersive virtual reality medical simulation: autonomous trauma training simulator. Cureus [Internet]. 2020 May 11 [cited 2022 Apr 25];12(5):e8062. Available from: https://pubmed.ncbi.nlm.nih.gov/32542120/ DOI: 10.7759/cureus.8062
47. De Ponti R, Marazzato J, Maresca AM, Rovera F, Carcano G, Ferrario MM. Pre-Graduation medical training including virtual reality during COVID-19 pandemic: ‘a report on students’ perception. BMC Med Educ [Internet]. 2020 Sep 25 [cited 2022 Apr 26]; 20(332):1-7. Available from: https://bmcmededuc.biomedcentral.com/track/pdf/10.1186/s12909-020-02245-8.pdf DOI: https://doi.org/10.1186/s12909-020-02245-8
48. Fertleman C, Aubugeau-Williams P, Sher C, Lim AN, Lumley S, Delacroix S, et al. A discussion of virtual reality as a new tool for training healthcare professionals. Front Public Health [Internet]. 2018 Feb 26 [cited 2022 Apr 18];6(44):1-5. Available from: https://www.frontiersin.org/articles/10.3389/fpubh.2018.00044/full DOI:10.3389/fpubh.2018.00044
49. Metro. [Internet]. Healthcare; 2022 [cited 2022 May 08]. Available from: https://www.metrocomms.co.uk/augmented-reality-for-health-professionals/
50. Craig Emory [Internet]. Check Out Snap’s AR Lens for COVID-19 Donations. Digital Bodies; 2020 [cited 2022 May 08]. Available from: https://www.digitalbodies.net/augmented-reality/snaps-ar-lens-for-COVID-19-donations/
51. Alyaqout K, AlQinai S, Almazeedi S, Karim JS, Al-Youha S, Al-Sabah S. Applying augmented reality to treat Fournier's gangrene in COVID-19 positive patients whilst safeguarding the multi-disciplinary surgical team: A case series. Int J Surg Case Rep [Internet]. 2021 Feb [cited 2022 Apr 27];79:335-338. Available from: https://pubmed.ncbi.nlm.nih.gov/33500878/ DOI:10.1016/j.ijscr.2021.01.055
52. Unberath M, Ghobadi K, Levin S, Hinson J, Hager GD. Artificial Intelligence-Based Clinical Decision Support for COVID-19–Where Art Thou? Advanced Intelligent Systems [Internet]. 2020 June [cited 2022 Sept 12];2(9). Available from: https://onlinelibrary.wiley.com/doi/full/10.1002/aisy.202000104 DOI: 10.1002/aisy.202000104
53. Uğur AR, Taşdelen A. COVID-19 PCR testi veri analizinde CAtenA Smart PCR Bioinformatik programının sunduğu ön değerlendirme sonuçlarının uzman sonuçları ile uyumunun araştırılması. European Journal of Science and Technology [Internet]. 2021 Aralık 1 [cited 2022 Nisan 15]; (29): 327-30. Available from: https://dergipark.org.tr/tr/pub/ejosat/issue/65857/1024190#article_cite DOI:10.31590/ejosat.1024190
54. Kart Ö, Basciftci F. Makine öğrenmesi algoritmalarıyla akciğer tomografi görüntülerinden COVID-19 tespiti. European Journal of Science and Technology [Internet]. 2021 Kasım 30 [cited 2022 Nisan 15]; (28):630-37. Available from: https://dergipark.org.tr/tr/pub/ejosat/article/1009611#article_cite DOI:10.31590/ejosat.1009611
55. Apostolopoulos ID, Aznaouridis S, Tzani M. Extracting possibly representative COVID-19 biomarkers from X-Ray images with deep learning approach and image data related to pulmonary diseases. J Med Biol Eng [Internet]. 2020 May 14 [cited 2022 Apr 19];(40):462-69. Available from: https://link.springer.com/article/10.1007/s40846-020-00529-4 DOI: https://doi.org/10.1007/s40846-020-00529-4
56. Song Y, Zheng S, Li L, Zhang X, Zhang X, Huang Z, et al. Deep learning enables accurate diagnosis of novel coronavirus (COVID-19) with CT images. IEEE/ACM Trans Comput Biol Bioinform [Internet]. 2021 Nov [cited 2022 Apr 21];18(6):2775-80. Available from: https://pubmed.ncbi.nlm.nih.gov/33705321/ DOI:10.1109/TCBB.2021.3065361
57. Beck BR, Shin B, Choi Y, Park S, Kang K. Predicting commercially available antiviral drugs that may act on the novel coronavirus (SARS-CoV-2) through a drug-target interaction deep learning model. Comput Struct Biotechnol J [Internet]. 2020 Mar [cited 2022 Apr 19];30(18):784-90. Available from: https://pubmed.ncbi.nlm.nih.gov/32280433/ DOI:10.1016/j.csbj.2020.03.025
58. Stebbing J, Phelan A, Griffin I, Tucker C, Oechsle O, Smith D, et al. COVID-19: combining antiviral and anti-inflammatory treatments. Lancet Infect Dis [Internet]. 2020 Apr [cited 2022 Apr 25];20(4):400-2. Available from: https://pubmed.ncbi.nlm.nih.gov/32113509/ DOI: 10.1016/S1473-3099(20)30132-8.
59. Lalmuanawma S, Hussain J, Chhakchhuak L. Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review. Chaos Solitons Fractals [Internet]. 2020 June [cited 2022 Apr 14];(139):110059. Available from: https://pubmed.ncbi.nlm.nih.gov/32834612/ DOI:10.1016/j.chaos.2020.110059
60. Akalın B, Veranyurt Ü. Sağlık Hizmetleri ve Yönetiminde Yapay Zekâ. Acta Infologica [Internet]. 2021 Nisan 20 [cited 2022 Nisan 21]; 5(1):232-39. Available from: https://dergipark.org.tr/tr/pub/acin/issue/63212/850857 DOI: 10.26650/acin.850857
61. Naudé W. Artificial Intelligence against Covid-19: An early eeview. IZA Discussion Paper No. 13110 [Internet]. 2020 Apr 6 [cited 2022 Apr 8]. Available from: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3568314 DOI:10.2139/ssrn.3568314.
62. Patel, Neel V. [Internet]. The best, and the worst, of the coronavirus dashboards; 2020. [cited 2022 May 01]. Available from: https://www.technologyreview.com/2020/03/06/905436/best-worst-coronavirus-dashboards/.
63. Qian Z, Alaa AM, van der Schaar M. CPAS: the UK's national machine learning-based hospital capacity planning system for COVID-19. Mach Learn [Internet]. 2020 Nov 24 [cited 2022 Apr 19];110(1):15-35. Available from: https://pubmed.ncbi.nlm.nih.gov/33250568/ DOI: 10.1007/s10994-020-05921-4
64. Cossio M ve Gilardino GE. Would the Use of Artificial Intelligence in COVID-19 Patient Management Add Value to the Healthcare System? Front. Med. [Internet]. 2021 Jan [cited 2022 Sept 12]; 8:619202 Available from: https://www.frontiersin.org/articles/10.3389/fmed.2021.619202/full DOİ: 10.3389/fmed.2021.619202
65. Philips. [Internet]. Philips launches next generation wearable biosensor for early patient deterioration detection, including clinical surveillance for COVID-19; 2020 [cited 2022 May 01]. Available from: https://www.philips.com/a-w/about/news/archive/standard/news/press/2020/20200526-philips-launches-next-generation-wearable-biosensor-for-early-patient-deterioration-detection-including-clinical-surveillance-for-COVID-19.html
66. Fdanews. [Internet]. FDA Clears Philips’ Disposable Patch for COVID-19 Patient Deterioration; 2020 [cited 2022 Apr 20]. Available from: https://www.fdanews.com/articles/print/197314-fda-clears-philips-disposable-patch-for-COVID-19-patient-deterioration
67. Triaxtec. [Internet]. In the Time of COVID-19 – How Will You Maintain Safe Working Distances?; n.d. [cited 2022 Apr 17]. Available from: https://www.triaxtec.com/resource/fact-sheet/proximity-trace/
68. Yousif M, Hewage C, Nawaf L. IoT Technologies during and beyond COVID-19: A comprehensive review. Future Internet [Internet]. 2021 Apr 23 [cited 2022 Apr 17];13(5):105. Available from: https://www.mdpi.com/1999-5903/13/5/105 DOI:10.3390/fi13050105
69. Kinsa. [Internet]. Thermometers; n.d. [cited 2022 Apr 12]. Available from: https://kinsahealth.com/thermometers
70. Rajeesh KNV, Arun M, Baraneetharan E, Jayaprakash JS, Kanchana A, Prabu S. Detection and monitoring of the asymptotic COVID-19 patients using IoT devices and sensors. International Journal of Pervasive Computing and Communications [Internet 9. 2020 Sep 23 [cited 2022 Apr 18]. Available from: https://www.emerald.com/insight/content/doi/10.1108/IJPCC-08-2020-0107/full/html DOI:10.1108/ijpcc-08-2020-0107
71. Misra S, Dep PK, Koppala N, Mukherjee A, Mao S. S-Nav: Safety-Aware IoT navigation tool for avoiding COVID-19 hotspots. IEEE Internet Things J [Internet]. 2021 Apr 15 [cited 2022 Apr 20];8(8):6975-82. Available from: https://ieeexplore.ieee.org/document/9257428 DOI:10.1109/jiot.2020.3037641
72. Vedaei SS, Fotovvat A, Mohebbian MR, Rahman GME, Wahid KA, Babyn P, et al. COVID-SAFE: An IoT-Based System for Automated Health Monitoring and Surveillance in Post-Pandemic Life. IEEE Access [Internet]. 2020 Oct 12 [cited 2022 Apr 14];8:188538-51. Available from: https://ieeexplore.ieee.org/document/9220167 DOI:10.1109/ACCESS.2020.3030194
73. Yousif M, Hewage C, Nawaf L. IOT technologies during and beyond COVID-19: A comprehensive review. Future Internet [Internet]. 21 Apr 23 [cited 2022 Sept 30];13(5):105. Available from: https://www.mdpi.com/1999-5903/13/5/105/htm DOI:10.3390/fi13050105
74. Al-Ogaili Ameer Alhasan S, Ramasamy A, Binti Marsadek A, Juhana Tengku Hashim M, Al-Sharaa T, Aadam A, et al. IoT technologies for tackling COVID-19 in Malaysia and worldwide: Challenges, recommendations, and proposed framework. Computers, Materials & Continua [Internet]. 2020 Nov 26 [cited 2022 Sept 30];66(2):2141–64. Available from: https://www.techscience.com/cmc/v66n2/40671 DOI: 10.32604/cmc.2020.013440
75. Chunming Z, He G. 5G Applications Help China Fight against COVID-19. China Academy of Information and Communications Technology [Internet]. 2020 [cited 2022 Apr 9]:1–4. Available from: http://www.caict.ac.cn/english/research/covid19/study/202004/P020200426371477971478.pdf
76. Kumar R, Pandey A, Ahmed AS, Fenta T, Genale AS, Alemu B. The role of 5G technology combatingcovid-19 pandemic and challenges for adoption. Ann Rom Soc Cell Biol [Internet]. 2021 May 6 [cited 2022 Apr 8];25(6):5370-78. Available from: https://annalsofrscb.ro/index.php/journal/article/view/6483
77. Wu S, Wu D, Ye R, Li K, Lu Y, Xu J, et al. Pilot study of robot-assisted teleultrasound based on 5G network: A new feasible strategy for early imaging assessment during COVID-19 pandemic. IEEE Trans Ultrason Ferroelectr Freq Control [Internet]. 2020 Nov [cited 2022 Apr 11];67(11):2241-48. Available from: https://pubmed.ncbi.nlm.nih.gov/32881685/ DOI:10.1109/TUFFC.2020.3020721
78. Siriwardhana Y, Gür G, Ylianttila M, Liyanage M. The role of 5G for digital healthcare against COVID-19 pandemic: opportunities and challenges. ICT Express [Internet]. 2021 June [cited 2022 Apr];7(2):244-52. Available from: https://www.sciencedirect.com/science/article/pii/S2405959520304744 DOI:10.1016/j.icte.2020.10.002
79. Qureshi HN, Manalastas M, Zaidi SMA, Imran A, Kalaa MOA. Service level agreements for 5G and beyond: overview, challenges and enablers of 5G-Healthcare systems. IEEE Access [Internet]. 2020 Dec 23 [cited 2022 Apr 9];9:1044-61. Available from: https://ieeexplore.ieee.org/abstract/document/9305243 DOI:10.1109/access.2020.3046927
80. Ahad A, Tahir M, Yau KLA. 5G-Based smart healthcare network: architecture, taxonomy, challenges and future research directions. IEEE Access [Internet]. 2019 Jul 23 [cited 2022 Apr 28];7:100747-62. Available from: https://ieeexplore.ieee.org/abstract/document/8769822 DOI:10.1109/access.2019.2930628.