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 Table of Contents  
Year : 2021  |  Volume : 11  |  Issue : 4  |  Page : 199-200

Advancement of multi-agent system in healthcare during COVID-19 pandemic

1 Department of Mechanical Engineering, I.K. Gujral Punjab Technical University, Hoshiarpur Campus, Hoshiarpur, Punjab, India
2 Department of Mechanical Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India
3 Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi, India

Date of Submission23-Nov-2020
Date of Acceptance06-Jul-2021
Date of Web Publication21-Aug-2021

Correspondence Address:
Dr. Shashi Bahl
Department of Mechanical Engineering, I.K. Gujral Punjab Technical University, Hoshiarpur Campus, Hoshiarpur - 146 001, Punjab
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/cmrp.cmrp_70_20

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How to cite this article:
Bahl S, Bagha AK, Javaid M, Haleem A. Advancement of multi-agent system in healthcare during COVID-19 pandemic. Curr Med Res Pract 2021;11:199-200

How to cite this URL:
Bahl S, Bagha AK, Javaid M, Haleem A. Advancement of multi-agent system in healthcare during COVID-19 pandemic. Curr Med Res Pract [serial online] 2021 [cited 2022 Sep 27];11:199-200. Available from: http://www.cmrpjournal.org/text.asp?2021/11/4/199/324255

Dear Editor,

A multi-agent system (MAS) is an efficient approach to combat the complex structure of the e-medicine system. The main features of the MAS are decentralization, flexibility, personalization, proactivity and security, which enable this platform of a patient to combat the pandemic. This system consists of a set of agents that divide a problem into sub-problems, which may be solved by these autonomous entities, for example, CARREL.[1] Based on the degree of the interdependency of tasks, agents may be concurrently running in various computers. The general performance of the system is improved; for example, health agents. MAS can change dynamically at runtime, for example, K4care. Personal agents associated with each patient may continuously monitor his/her medical information and raise the appropriate alarms when a problem is detected; for example, GerAmI and Aingeru.[2],[3]

[Figure 1] represents the MAS process for the treatment of COVID-19 patients. [Figure 1] also shows how the patient goes through the admission and treatment process. If the patient does not have a badge, the data recorded during its transition at bed reservation service are verified and completed. A hospitalisation badge is then given to the patient, this contains data related to his/her stay, and then, all the data will be displayed on healthcare worksheets. If the patient has a valid hospitalisation badge, then he/she will go to the concerning care units (CUs). Medical staff indicates all the related information regarding a patient, his/her symptoms and all the necessary test reports for COVID-19 on designed healthcare worksheets. Once the treatments in the CU are finished, then the patient goes for other medico-technical examination. On being tested positive for coronavirus, appropriate treatment of the patient is started. This treatment changes as per the condition of the patient. On completing the treatment process, the patient is re-tested for COVID-19, and if the patient is tested negative, then he/she will be discharged. MAS is Industry 4.0 Technology, and some Industry 4.0 technologies are already discussed in context of COVID-19 pandemic.[4],[5],[6],[7],[8],[9]
Figure 1: Multi-agent system enabled process for the treatment of patients during COVID-19 pandemic

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MAS deals with multiple sources of data. These data should be appropriately modified to gain sufficient health and medical records to support medical decisions. Healthcare services, a distributed agent-based platform, are used to provide healthcare service to patients and professionals who are practicing.[10],[11],[12] It allows healthcare professionals to execute clinical guidelines. In MAS, each patient is provided with personal agents. Hence, personal agent associated with the patient is continuously monitored.

This system is an agent-based system that can be applied during this crisis in medical data management. It develops various interfaces to combine the existing information system. A MAS ceaselessly monitors patient and medical contact centers simultaneously. SHARE-it (Supported Human Autonomy for Recovery Enhancement of cognitive and motor disabilities using agent technologies) provides a collaboration of the MAS with other technologies to produce e-tools for persons with physical disorders and senior citizens. K4care platform is a multi-agent–based system that provides e-services to caregivers and patients. In the future, MAS will become a powerful approach that could solve various healthcare problems.

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Conflicts of interest

There are no conflicts of interest.

  References Top

Cortés U, Vázquez-Salceda J, López-Navidad A, Caballero F. UCTx: A multi-agent system to assist a transplant coordination unit. Appl Intell 2004;20:59-70.  Back to cited text no. 1
Bagues MI, Bermudez J, Burgos A, Goni A, Illarramendi A, Rodriguez J, et al. An Innovative System that Runs on a PDA for a Continuous Monitoring of People. In: 19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06); 2006:151-156. doi:10.1109/CBMS.2006.40.  Back to cited text no. 2
Corchado JM, Bajo J, Abraham A. GerAmi: Improving healthcare delivery in geriatric residences. IEEE Intell Sys 2008;23:19-25.  Back to cited text no. 3
Javaid M, Haleem A, Vaishya R, Bahl S, Suman R, Vaish A. Industry 4.0 technologies and their applications in fighting COVID-19 pandemic. Diabetes and Metabolic Syndrome. Clin Res Rev 2020;14:419-22.  Back to cited text no. 4
Iyengar K, Bahl S, Vaishya R, Vaish A. Challenges and solutions in meeting up the urgent requirement of ventilators for COVID-19 patients. Diabetes Metab Syndr 2020;14:499-501.  Back to cited text no. 5
Vaishya R, Bahl S, Singh RP. Letter to the editor in response to: Telemedicine for diabetes care in India during COVID19 pandemic and national lockdown period: Guidelines for physicians. Diabetes Metab Syndr 2020;14:687-8.  Back to cited text no. 6
Bahl S, Singh RP, Javaid M, Khan IH, Vaishya R, Suman R. Telemedicine technologies for confronting COVID-19 pandemic: A Review. J Ind Integr Manag Innov Entrep 2020;5:547-61. doi:10.1142/S2424862220300057.  Back to cited text no. 7
Bahl S, Javaid M, Bagha AK, Singh RP, Haleem A, Vaishya R, et al. Biosensors applications in fighting COVID-19 pandemic. Apollo Med 2020;17:221-3.  Back to cited text no. 8
  [Full text]  
Sharma A, Bahl S, Bagha AK, Javaid M, Shukla DK, Haleem A. Blockchain technology and its applications to combat COVID-19 pandemic. Res Biomed Eng. Published online 2020:1-8. doi:10.1007/s42600-020-00106-3.  Back to cited text no. 9
Singh RP, Javaid M, Haleem A, Vaishya R, Bahl S. Significance of Health Information Technology (HIT) in context to COVID-19 pandemic: Potential roles and challenges. J Ind Integr Manag. 2020;5:427-40. doi:10.1142/S2424862220500232.  Back to cited text no. 10
Sharma A, Bahl S, Bagha AK, Javaid M, Shukla DK, Haleem A. Multi-Agent System Applications to Fight COVID-19 Pandemic. Apollo Med. 2020;17:41-3.  Back to cited text no. 11
Kushwaha S, Bahl S, Bagha AK, Parmar KS, Javaid M, Haleem A, et al. Significant Applications of Machine Learning for COVID-19 Pandemic. J Ind Integr Manag. 2020;5:453-79.  Back to cited text no. 12


  [Figure 1]

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