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An Overview of Intelligent Diagnosis and Prediction Methods for COVID-19 Using Machine Learning and Deep Learning Techniques
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Abstract: (315 Views) |
| The COVID-19 disease, which originates from the coronavirus family, has turned into a global pandemic and has had many adverse individual and social effects. This disease has impacted various individual aspects such as health, immunity, and well-being, as well as social aspects like economic losses, unemployment, and inadequate medical resources. The most fundamental and primary method for controlling COVID-19 to reduce its negative effects is the timely diagnosis of this disease to decrease mortality rates and control its outbreak. In the field of COVID-19 diagnosis, researchers have employed various methods, the majority of which utilize CT scan images and chest X-rays, with the overall architecture of most models based on data mining techniques, including machine learning and deep learning methods. The aim of this paper is to review methods based on machine learning and deep learning techniques for predicting COVID-19. Research results indicate that deep learning finds approximate solutions faster in detecting COVID-19 compared to traditional data mining algorithms and precise methods, and generally provides better results compared to deterministic algorithms. |
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| Keywords: COVID-19 disease, intelligent diagnosis and prediction, data mining, machine learning techniques, deep learning. |
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Full-Text [PDF 540 kb]
(140 Downloads)
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Type of Study: Scientific-extension |
Subject:
Special
Received: 2025/06/1 | Accepted: 2025/03/5 | Published: 2025/03/5
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