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COVID-19 prediction using AI analytics for South Korea
1Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, Sector-62, Noida, Uttar Pradesh India.
Applied Intelligence (Dordrecht, Netherlands)
|November 12, 2021
Summary
This study analyzed COVID-19's demographic impact, finding age significantly increases mortality risk, especially for those 60-80. Machine learning models predict survival chances for infected individuals.
Area of Science:
- Epidemiology
- Public Health
- Data Science
Background:
- The COVID-19 pandemic presented a global public health emergency.
- Understanding demographic factors influencing spread and mortality is crucial.
Purpose of the Study:
- To analyze demographic factors affecting COVID-19 spread and mortality.
- To develop an AI-based model for predicting survival chances in South Korea.
- To assess the impact of age, gender, and temporal factors on disease outcomes.
Main Methods:
- Demographical analysis of global pandemic spread and mortality.
- Cluster-based analysis of age groups.
- Application of machine learning and deep learning models with hyperparameter tuning and autoencoder approach.
- Statistical analysis of exploratory factors for survival prediction.
Main Results:
- Mortality rates increase with age, with the highest death cases in the 60-80 age group.
- Association between positive COVID-19 cases and deceased cases identified, with gender-specific impacts.
- AI models effectively predicted survival chances for quarantined patients in South Korea.
- Machine intelligence and deep learning models provided a quantitative view of the outbreak.
Conclusions:
- Age is a critical factor in COVID-19 mortality.
- AI and deep learning are valuable tools for analyzing epidemic outbreaks and predicting patient outcomes.
- The study offers insights into temporal trends and impactful features of the pandemic.
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