Investigating New Patterns in Symptoms of COVID-19 Patients by Association Rule Mining (ARM)

Authors

  • Anju Singh Sage University, Bhopal, Madhya Pradesh, India
  • Divakar Singh UIT, Barkatullah University, Bhopal, Madhya Pradesh, India
  • Kamal Upreti Dr Akhilesh Das Gupta Institute of Technology & Management, New Delhi, India
  • Vaibhav Sharma SGRR School of CA &IT, SGRR University Dehradun, India
  • Bhawani Singh Rathore UIT, Barkatullah University, Bhopal, Madhya Pradesh, India
  • Jagdish Raikwal Institute of Engineering and Technology, Devi Ahilya University, Indore, India

DOI:

https://doi.org/10.13052/jmm1550-4646.1911

Keywords:

COVID-19, hotspot, segments, association rule mining (ARM), customer behavior analysis, market basket analysis, pattern, world health organization (WHO)

Abstract

Background: COVID-19 is a major public health emergency wreaking havoc on public health, happiness, and liberty of travel, as well as the worldwide economy. Scientists from all over the world are working to develop treatments and vaccines; the WHO has given emergency approval to eight vaccines from around the world. However, it is also seen that the efficiency of vaccines is not up to the mark in different age groups. COVID-19 symptoms come in many different shapes and sizes, so it’s important to learn about them as soon as possible so that medical attention and management can be easier.

Method: The GitHub Data Repository-made COVID-19 patient data is available on the internet, which is used in this investigation. We have used the association rule mining method to look for common patterns in a targeted class or segment and then look at the symptoms based on them.

Result: The result is that this study involves individuals with a median age of 52 years old. Few frequent symptoms like respiratory failure (1%), septic shock (1.4%), respiratory distress syndrome (1.8%), diarrhoea (1.8%), nausea (2%), sputum (3%), headache (5%), sore throat (8%), pneumonia (8%), weakness (7%), malaise/body pain (11%), cough (37%), fever (67%) and remaining diseases like myocardial infarction, cardiac failure, and renal illness (less than 1%) were present. If a patient had chronic disease, respiratory failure, and pneumonia, there was a higher risk of death; if a patient had a combination of chronic disease, respiratory failure, and pneumonia, respiratory failure in the age range of 45 to 84 years there was a higher risk of death. Patients having chronic conditions like pneumonia or renal disease symptoms that died as a result of the corona virus had more serious indication patterns than those without chronic diseases.

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Author Biographies

Anju Singh, Sage University, Bhopal, Madhya Pradesh, India

Anju Singh is working as an Associate Professor, Sage University, Bhopal Madhya Pradesh, India. Till now 60 M. Tech dissertations guided by her and 57++ Research papers were published. Her Google research scholar total citations are 202, h-index is 09 and i-index is 08. She has filed one international patent. She has more than 15 years of experience in both teaching and research. She was honored by the Session Chair/Technical Committee Member on National and International conferences. She is a life member of ISTE and CSI and a fellow IETE. Her area of interest includes Deep learning, image processing, nature-inspired algorithms and soft computing.

Divakar Singh, UIT, Barkatullah University, Bhopal, Madhya Pradesh, India

Divakar Singh is working as an Assistant Professor at University Institute of Technology, Barkatullah University, Bhopal, and Madhya Pradesh, India. He got ranked in the Top 50 head of the department CSE/IT award in all India level for session 2019–20 by uLektz Wall Of Fame. Till now 91 M. Tech and 1 PhD, dissertation guided by him and 130++ Research papers were published. His Google research scholar total citations are 420, h-index is 11 and i-index is 15. He has more than twenty years of experience in both teaching and research. He has served as a Head of the department, in Computer Science and Engineering since 2006 in UIT, Barkatullah University. He has worked as a member of board of studies and as a chairman of, board of studies in the subject CSE/IT/Electronics in the Faculty of Engineering. His area of interest includes Deep learning, image processing, nature-inspired algorithms and soft computing.

Kamal Upreti, Dr Akhilesh Das Gupta Institute of Technology & Management, New Delhi, India

Kamal Upreti is currently working as an Associate Professor in the Department of Information Technology, Dr. Akhilesh Das Gupta Institute of Technology & Management, Delhi. He completed is B. Tech (Hons), M. Tech (Gold Medalist), PGDM(Executive) and PhD in Computer Science & Engineering.

He has published 50++ patents, 32++ books, 15++ magazine issues and 30++ research papers in various reputed international Journals and Conferences. His areas of research interest include Machine Learning, Wireless Networking, Embedded System and Cloud Computing. He has been chaired many sessions in National and International Conferences across the globe.

Vaibhav Sharma, SGRR School of CA &IT, SGRR University Dehradun, India

Vaibhav Sharma is working as an Assistant Professor in School of Computer Application & Information Technology at SGRR University Dehradun, India since 2013. He has total 12++ years of teaching experience in various Institutes and Universities. He has qualified UGC NET and USET. He is pursuing his PhD in Computer Science. He has published Three Patents, Two Books, and Five Research Papers in national, international journals and conferences and achieved Five best Teacher and Research Excellence awards. He has also participated in many national and international Conferences, Workshops, Webinars, FDP, STC etc. His areas of interest include Programming in C, C# with .Net Framework, RDBMS, Design and Analysis of Algorithms, Python, IOT etc.

Bhawani Singh Rathore, UIT, Barkatullah University, Bhopal, Madhya Pradesh, India

Bhawani Singh Rathore is working as a Guest Faculty at University Institute of Technology, Barkatullah University, Bhopal, and Madhya Pradesh, India. He is having 5 years of teaching experience. He has worked as a Teacher Guardian at UIT, Barkatullah University. He has delivered an Expert lecture in AWS and Google Cloud Chatbot. He has attended FDP at NIT Kurukshetra and NITTTR Chennai. His area of interest includes Google Clouds, Data Mining, and Web APIs.

Jagdish Raikwal, Institute of Engineering and Technology, Devi Ahilya University, Indore, India

Jagdish Raikwal is Assistant Professor in the Department of Information Technology at Institute of Engineering & Technology, Devi Ahilya University, Indore. He is having more than 12 years of teaching experience. He has more than 26 research publications in various pre-reviewed Journal and Conferences.

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Published

2022-08-25

How to Cite

Singh, A. ., Singh, D. ., Upreti, K. ., Sharma, V. ., Rathore, B. S. ., & Raikwal, J. . (2022). Investigating New Patterns in Symptoms of COVID-19 Patients by Association Rule Mining (ARM). Journal of Mobile Multimedia, 19(01), 1–28. https://doi.org/10.13052/jmm1550-4646.1911

Issue

2023: Vol 19 Iss 1

Section

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