Selected article for: "acute pneumonia and machine learning"

Author: Sarkar, O.; Ahamed, M. F.; Chowdhury, P.; Ieee,
Title: Forecasting & Severity Analysis of COVID-19 Using Machine Learning Approach with Advanced Data Visualization
  • Cord-id: 30c7j669
  • Document date: 2020_1_1
  • ID: 30c7j669
    Snippet: SARS-CoV-2 (n-coronavirus) is a global pandemic that causes the deaths of millions of people worldwide. It can cause Pneumonia and severe acute respiratory syndrome (SARS) and lead to death in severe cases. It is an asymptomatic disease that hardens our life and work conditions. As there is no effective treatment available, many scientists and researchers are trying their best to fight the pandemic. This paper focused on the coronavirus pandemic situation in the global and Bangladesh region and
    Document: SARS-CoV-2 (n-coronavirus) is a global pandemic that causes the deaths of millions of people worldwide. It can cause Pneumonia and severe acute respiratory syndrome (SARS) and lead to death in severe cases. It is an asymptomatic disease that hardens our life and work conditions. As there is no effective treatment available, many scientists and researchers are trying their best to fight the pandemic. This paper focused on the coronavirus pandemic situation in the global and Bangladesh region and its related effects and future status. We have utilized different information representation and machine learning calculations to recreate the affirmed, recuperated, and passing cases. We believe the research will help scientists, researchers, and ordinary people predict and analyze this pandemic's impact. Finally, the comparison and analysis of different models and algorithms successfully showed our visualization and prediction success.

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