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Volume 1 , Issue 2 , PP: 37-47, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Abdelhameed Ibrahim 1 *
Doi: https://doi.org/10.54216/MOR.010204
This systematic review explores the use of artificial intelligence (AI) and machine learning (ML) during the COVID-19 disease outbreak. AI/ML models may interpret medical images, auditory input, and patient records to diagnose early enough, thus enhancing the likelihood of positive patient outcomes. Coupled with optimization algorithms, deep learning methods have predicted COVID-19 from chest X-rays and CT scans with unprecedented high accuracy. This review, therefore, synthesizes the existing literature and looks at the significant emphases, gaps, and potential trends of applying AI in diagnosing COVID-19 and forecasting outbreaks. Further, the advancement of AI and ML in this domain needs to be known to enhance global preventive diagnostic techniques for future pandemics.
AI , ML , Covid-19 Detection , Deep Learners , CNN , Chest X-ray
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