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Review on COVID-19 diagnosis models based on machine learning and deep learning approaches.
Zaid Abdi Alkareem Alyasseri1,2, Mohammed Azmi Al-Betar3,4, Iyad Abu Doush5,6
1Center for Artificial Intelligence Technology, Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia.
Expert Systems
|September 13, 2021
Summary
This review examines deep learning (DL) and machine learning (ML) for COVID-19 diagnosis. Support Vector Machines (SVM) and Convolutional Neural Networks (CNN) are the most effective ML and DL methods, respectively, for accurate diagnosis and outbreak prediction.
Area of Science:
- Medical Informatics
- Artificial Intelligence
- Epidemiology
Background:
- The COVID-19 pandemic, caused by SARS-CoV-2, has overwhelmed traditional diagnostic methods due to rapid global spread.
- Intelligent techniques like deep learning (DL) and machine learning (ML) offer promising solutions for rapid and accurate COVID-19 diagnosis.
Purpose of the Study:
- To provide a comprehensive review of recent DL and ML techniques applied to COVID-19 diagnosis.
- To classify research into DL and ML categories and analyze public COVID-19 datasets.
- To guide future research and development in ML and DL for COVID-19 diagnostics and outbreak prediction.
Main Methods:
- Systematic review of over 200 studies published between December 2019 and April 2021 from major publishers.
- Classification of selected research into Deep Learning (DL) and Machine Learning (ML) categories.
- Comparative analysis of evaluation metrics, including accuracy, sensitivity, and specificity, across various diagnostic methods.
Main Results:
- Support Vector Machine (SVM) is the most frequently utilized ML algorithm for COVID-19 diagnosis and outbreak prediction.
- Convolutional Neural Network (CNN) is the most prevalent DL mechanism for COVID-19 diagnosis.
- Accuracy, sensitivity, and specificity are the most common metrics for evaluating diagnostic performance.
Conclusions:
- ML and DL techniques, particularly SVM and CNN, show significant potential for efficient COVID-19 diagnosis and outbreak prediction.
- The review highlights the importance of established public datasets and standardized evaluation metrics.
- This work serves as a guide for researchers, encouraging further innovation in AI-driven healthcare solutions for infectious diseases.
