Empowering Healthcare with Machine Learning: A Comprehensive Review of Machine Learning- based COVID-19 Detection, Diagnosis and Treatment
Abstract
The COVID-19 pandemic has raised significant concerns due to its unique nature and potential for severe illness and death. This article discusses machine learning, a technique that extracts patterns from complex data and offers potential solutions to the pandemic’s issues. Machine learning systems can identify COVID-19 from various sources, forecast case severity, and identify individuals at high risk of complications. Diagnostic methods based on machine learning can reliably categorise COVID-19 cases and rule out other illnesses. Personalised treatment regimens are being developed using machine learning, which can improve patient outcomes and reduce side effects. However, challenges such as large datasets, complexity of models, and regulatory clearance for machine learning-based applications must be overcome. Despite these challenges, machine learning has the potential to revolutionise COVID-19 identification, diagnosis, and treatment. Thus, as the technology behind machine learning continues to progress, we can anticipate the appearance of even more cutting-edge applications that will assist us in containing this epidemic and saving lives.
How to cite this article:
Walia RK, Kaur H. Empowering Healthcare with
Machine Learning: A Comprehensive Review of
Machine Learning-based COVID-19 Detection,
Diagnosis and Treatment. J Adv Res Med Sci
Tech. 2023;10(3&4):1-3.
DOI: https://doi.org/10.24321/2394.6539.202303
How to cite this article:
Walia RK, Kaur H. Empowering Healthcare with Machine Learning: A Comprehensive Review of Machine Learning-based COVID-19 Detection, Diagnosis and Treatment. J Adv Res Med Sci
Tech. 2023;10(3&4):6-8.
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