Title: Analysis of COVID-19 symptoms using machine learning and robotic process automation

Authors: Gireesh Kumar; Richa Sharma

Addresses: Department of CSE, Manipal University Jaipur, Jaipur-303007, India ' Department of Mathematics, JK Lakshmipat University, Jaipur-302026, India

Abstract: A virus called coronavirus or COVID-19 is the source of the contagious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease quickly spread worldwide, resulting in the COVID-19 pandemic. The virus is caused by beta coronavirus strain which is an acute SARS-CoV-2. The contagiousness of the virus resulted in universal infections and deaths since medically proven treatment was not available. The primary clinical symptoms are fever, cough, sore throat, shortness of breath and headache. This study aims to train a model using machine learning (ML) and robotics process automation (RPA) to predict infections, analyse symptoms and predict vulnerability. This study analyses the symptoms to determine clinical significance and rank the symptoms based on their significance and gender. Additionally, the model studies the effect of age on vulnerability towards infection. By automating the symptom analysis process, we aim to improve the efficiency and accuracy of COVID-19 diagnosis, ultimately aiding healthcare professionals in making informed decisions. The integration of ML and RPA holds the potential to revolutionise how healthcare systems address not only the current COVID-19 crisis but also future challenges in the rapidly evolving landscape of infectious diseases.

Keywords: clinical; symptom; pandemic; machine learning; ML; robotics process automation; RPA.

DOI: 10.1504/IJCVR.2026.151539

International Journal of Computational Vision and Robotics, 2026 Vol.16 No.2, pp.246 - 256

Received: 11 May 2023
Accepted: 26 Nov 2023
Published online: 05 Feb 2026 *

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