A Comprehensive Exploration of Artificial Intelligence Methods for COVID-19 Diagnosis

Abstract

INTRODUCTION: The 2019 COVID-19 pandemic outbreak triggered a previously unseen global health crisis demanding accurate diagnostic solutions. Artificial Intelligence has emerged as a promising technology for COVID-19 diagnosis, offering rapid and reliable analysis of medical data. OBJECTIVES: This research paper presents a comprehensive review of various artificial intelligence methods applied for the diagnosis, aiming to assess their effectiveness in identifying cases, predicting disease progression and differentiating from other respiratory diseases. METHODS: The study covers a wide range of artificial intelligence methods and with application in analysing diverse data sources like chest x-rays, CT scans, clinical records and genomic sequences. The paper also explores the challenges and limitations in implementing AI -based diagnostic tools, including data availability and ethical considerations. CONCLUSION: Leveraging AI’s potential in healthcare can significantly enhance diagnostic efficiency crisis management as the pandemic evolves.