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Combating COVID-19 Crisis using Artificial Intelligence (AI) Based Approach: Systematic Review.

Kavya Singh¹, Navjeet Kaur², Ashish Prabhu³

¹Department of Biotechnology, Banasthali University, Banasthali Vidyapith, Banasthali, 304022, Rajasthan, India.

Current Topics in Medicinal Chemistry

|February 6, 2024

Summary

Artificial intelligence (AI) and machine learning (ML) offer powerful tools for combating COVID-19, aiding in early detection, diagnosis, and drug development. This review highlights AI

Keywords:

Artificial intelligence COVID-19 and CT-scan images Deep learning Disease diagnostics.Drug research Machine learning Vaccine development X-ray

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Area of Science:

Medical Informatics
Computational Biology
Epidemiology

Background:

The COVID-19 pandemic necessitated innovative solutions, leading to the adoption of artificial intelligence (AI) and machine learning (ML) techniques.
AI/ML tools have been instrumental in addressing complex challenges posed by the pandemic, from diagnostics to public health interventions.

Purpose of the Study:

To evaluate the role of AI in combating COVID-19, focusing on detection, diagnostics, mortality prediction, and vaccine/drug development.
To provide a comprehensive review of AI applications in managing the COVID-19 outbreak.

Main Methods:

A systematic literature search was conducted using PRISMA guidelines across PubMed, Web of Science, and Science Direct.
Search terms included "COVID-19" and AI-specific keywords, covering publications from December 2019 to August 2023.

Main Results:

Out of 961 articles, 135 were selected for review, focusing on AI applications in COVID-19.
Key areas included detection/diagnosis (60 papers), mortality prediction (19 papers), vaccine/drug development (22 papers), and pandemic control.

Conclusions:

AI-based methodologies provide valuable insights into various aspects of COVID-19 research.
The findings highlight essential data types and tools that can facilitate medical and translational research for future outbreaks.