Machine learning approach for confirmation of COVID-19 cases: positive, negative, death and release
Journal Title: Iberoamerican Journal of Medicine - Year 2020, Vol 2, Issue 3
Abstract
Introduction: Corona Virus Infectious Disease (COVID-19) is the infectious disease. The COVID-19 disease came to earth in early 2019. It is expanding exponentially throughout the world and affected an enormous number of human beings starting from the last month. The World Health Organization (WHO) on March 11, 2020 declared COVID-19 was characterized as “Pandemic”. This paper proposed approach for confirmation of COVID-19 cases after the diagnosis of doctors. The objective of this study uses machine learning method to evaluate how much predicted results are close to original data related to Confirmed-Negative-Released-Death cases of COVID-19. Materials and methods: For this purpose, a verification method is proposed in this paper that uses the concept of Deep-learning Neural Network. In this framework, Long shrt-term memory (LSTM) and Gated Recurrent Unit (GRU) are also assimilated finally for training the dataset. The prediction results are tally with the results predicted by clinical doctors. Results: The results are obtained from the proposed method with accuracy 87 % for the “confirmed Cases”, 67.8 % for “Negative Cases”, 62% for “Deceased Case” and 40.5 % for “Released Case”. Another important parameter i.e. RMSE shows 30.15% for Confirmed Case, 49.4 % for Negative Cases, 4.16 % for Deceased Case and 13.72 % for Released Case. Conclusions: The outbreak of Coronavirus has the nature of exponential growth and so it is difficult to control with limited clinical persons for handling a huge number of patients within a reasonable time. So it is necessary to build an automated model, based on machine learning approach, for corrective measure after the decision of clinical doctors.
Authors and Affiliations
Shawni Dutta, Samir Kumar Bandyopadhyay
Keywords
Related Articles
- EP ID EP684602
- DOI https://doi.org/10.5281/zenodo.3822623
- Views 204
- Downloads 0
Quantitative immunohistochemical expression of GP88 in invasive ductal carcinoma (IDC) of human breast cancer
Introduction: Progranulin or acrogranin is an 88-kDa glycoprotein identified by a biological screen for protein targets associated with high tumorigenicity. This work was aimed to investigate the digital expression of GP...
Primary Cicatricial Alopecia among Lybian patients: A Clinicopathological and Epidemiological study
Introduction: Cicatricial alopecias are a group of disorders characterized by hair follicle destruction with the consequence of permanent hair loss. The current study was conducted to evaluate the epidemiological and cli...
Effective stakeholder analysis and engagement: a vital strategy for enhanced pharmacovigilance systems in sub-Saharan Africa
..........
Implementation of good pharmacy practice standards; a step forward in Libya’s pharmacies
The practice of pharmacy in health care societies continues to undergo evolutionary and even radical changes. It has changed to a personal health service charged with assuring pharmaceutic and therapeutic appropriateness...
How to Design and Apply an Objective Structured Clinical Examination (OSCE) in Medical Education?
The Objective Structured Clinical Examination (OSCE) is considered a gold standard summative and formative assessment method wherein it is a comprehensive and standardized tool assessing the clinical competencies includi...