The Impacts of Various Machine Learning Methods for Effective Pandemic Management: A Review
Authors
WAJID KHAN, KALSOOM AYYAZ, SYED ZOHAIB HASSAN, GOHAR ZAMAN, AYESHA IRSHAD and MUHAMMAD AYYAZ
Abstract
The unexpected outbreak of COVID19 affected the world deeply in terms of social as well as economical. It's been almost two years passed still the pandemic is uncontrollable. Most underdeveloped countries fail to respond this critical situation due to a lack of resources as well as improper health care system. This pandemic had also raised the questions about the preparation of the health care system for any other outbreak. There have been several suggestions to manage any type of pandemic properly and effetely in future by using the new advancement medical science and specially using of technologies like artificial intelligence (AI) and machine learning (ML). This paper will review some state-of-the-art artificial intelligence (AI) and machine learning (ML) tools for pandemic management. As we know that ML models have handled the multidimensional, large volume of real-time data related to pandemic management. These models are very well suited for prediction, classification, and recognition problems. ML models now plays a key role in pandemic management, such as pandemic prediction, people surveillance, risk management, medical diagnosis, and screening. This article presents an overview of pandemics, reviewing some ML models and their application in pandemic management. The last section discusses the challenges and future research.