A Comprehensive Review of Machine Learning Used to Combat COVID-19

Area of Science:

• Medical Informatics
• Artificial Intelligence in Healthcare
• Computational Biology

Background:

• The COVID-19 pandemic caused over 6.3 million deaths globally.
• Artificial Intelligence (AI) solutions have become crucial for managing the pandemic.
• AI aids in diagnosis, treatment, and understanding the disease's long-term effects.

Purpose of the Study:

• To review AI methods and modeling efforts applied to COVID-19.
• To highlight AI's role in diagnosis, prognosis, and resource optimization.
• To explore the future trajectory of AI in combating infectious diseases.

Main Methods:

• Review of AI applications in medical image analysis (identification, classification, segmentation).
• Exploration of AI-driven prognostic models for health outcomes.
• Analysis of AI in longitudinal studies for understanding disease progression.

Main Results:

• AI models demonstrate effectiveness in analyzing medical images for COVID-19 detection.
• Prognostic AI models aid in predicting patient outcomes and resource management.
• AI facilitates a deeper understanding of COVID-19's long-term patient impact.

Conclusions:

• AI plays a pivotal role in the ongoing fight against COVID-19.
• AI advancements are crucial for future pandemic preparedness and response.
• The integration of AI in healthcare is essential for tackling complex global health challenges.