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





Machine Learning, COVID-19, Disease Diagnosis, Artificial Intelligence


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.


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How to Cite

S B, M A, K SK, Dhanaraj RK. A Comprehensive Exploration of Artificial Intelligence Methods for COVID-19 Diagnosis. EAI Endorsed Trans Perv Health Tech [Internet]. 2024 Feb. 21 [cited 2024 Apr. 25];10. Available from: https://publications.eai.eu/index.php/phat/article/view/5174