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Towards classification and comprehensive analysis of AI-based COVID-19 diagnostic techniques: A survey
Amna Kosar1, Muhammad Asif1, Maaz Bin Ahmad2
1Department of Computer Science, Lahore Garrison University, Lahore, Pakistan.
Insights
This review systematically analyzes COVID-19 diagnostic techniques, including imaging, PCR, and antigen tests. Artificial Intelligence significantly enhances diagnostic capabilities, offering valuable tools for healthcare systems and future pandemics.
Area of Science:
- Medical Diagnostics
- Infectious Diseases
- Artificial Intelligence in Healthcare
Background:
- The COVID-19 pandemic, caused by the novel coronavirus, emerged in late 2019, leading to significant global health and economic impacts.
- Over 600 million cases and 6.6 million deaths were reported worldwide by November 2022.
- Diverse diagnostic techniques were developed to combat the rapid spread of the virus.
Purpose of the Study:
- To conduct a systematic review of various COVID-19 diagnostic techniques.
- To classify and comparatively analyze the efficacy of different diagnostic modalities.
- To highlight the role of Artificial Intelligence in advancing COVID-19 diagnostics.
Main Methods:
- Systematic review of COVID-19 diagnostic techniques.
- Classification based on working principles: chest X-ray imaging, cough sound analysis, RT-PCR, antigen testing, and antibody testing.
- Comparative analysis of the efficacy of each diagnostic method.
Main Results:
- Diagnostic techniques were categorized into imaging, respiratory pattern analysis, molecular tests (RT-PCR), and serological tests (antigen/antibody).
- Artificial Intelligence (AI) emerged as a crucial element in developing advanced diagnostic tools.
- The review provides a comprehensive overview for researchers and supports healthcare systems.
Conclusions:
- AI plays a vital role in enhancing the accuracy and efficiency of COVID-19 diagnostics.
- The reviewed techniques offer lasting solutions applicable to future pandemic scenarios.
- This consolidated information serves as a valuable resource for ongoing research and development in diagnostic technologies.
Abstract:
The unpredictable pandemic came to light at the end of December 2019, known as the novel coronavirus, also termed COVID-19, identified by the World Health Organization (WHO). The virus first originated in Wuhan (China) and rapidly affected most of the world's population. This outbreak's impact is experienced worldwide because it causes high mortality risk, many cases, and economic falls. Around the globe, the total number of cases and deaths reported till November 12, 2022, were >600 million and 6.6 million, respectively. During the period of COVID-19, several diverse diagnostic techniques have been proposed. This work presents a systematic review of COVID-19 diagnostic techniques in response to such acts. Initially, these techniques are classified into different categories based on their working principle and detection modalities, i.e. chest X-ray imaging, cough sound or respiratory patterns, RT-PCR, antigen testing, and antibody testing. After that, a comparative analysis is performed to evaluate these techniques' efficacy which may help to determine an optimum solution for a particular scenario. The findings of the proposed work show that Artificial Intelligence plays a vital role in developing COVID-19 diagnostic techniques which support the healthcare system. The related work can be a footprint for all the researchers, available under a single umbrella. Additionally, all the techniques are long-lasting and can be used for future pandemics.
