Indispensable role of Artificial Intelligence in COVID-19 Diagnosis and Prediction: A Thematic Narrative Review

Abstract

Background: The COVID-19 pandemic created unprecedented challenges for healthcare systems worldwide, accelerating the adoption of Artificial Intelligence (AI) for diagnosis and prediction. AI has emerged as a valuable tool for enhancing the global response to the pandemic.
Objective: This thematic narrative review synthesizes published literature on the applications of Artificial Intelligence in diagnosis and prediction of COVID-19.
Methods: Relevant literature published between 2020 and 2022 was reviewed and synthesized using a thematic narrative approach. The selected studies were examined to identify major trends and applications of Artificial Intelligence in addressing challenges associated with the pandemic.
Results: The reviewed literature was organized into three thematic areas: (1) the indispensable role of AI in pandemic management, (2) AI as a paradigm shift in COVID-19 diagnosis, and (3) AI in COVID-19 prediction. The findings indicate that deep learning architectures, particularly Convolutional Neural Networks (CNNs), demonstrated high accuracy in identifying COVID-19 cases through medical image analysis. Furthermore, machine learning and deep learning models effectively supported disease forecasting, patient risk assessment, outcome prediction, and healthcare resource planning.
Conclusion: Artificial Intelligence has demonstrated significant potential in addressing challenges related to COVID-19, offering innovative solutions for diagnosis and prediction. Future efforts should focus on the clinical validation, implementation, and integration of these technologies into standard public health infrastructure to enhance preparedness for future outbreaks.