Artificial intelligence as a powerful tool in overcoming substantial health problems of the COVID-19 pandemic
Introduction This review aims to investigate modern methods of applying artificial intelligence to diagnose SARS Cov-2 and predict the development of potential emergencies. Methods The most commonly used electronic databases, such as Scopus and Medline during 2020, were searched. A narrative approac...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN SR |
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Serbian Medical Society - Dental Section, Belgrade
2021
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| Acceso en línea: | https://doaj.org/article/8d9cd040282946eaa2ac17bfa1a41c35 |
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| Sumario: | Introduction This review aims to investigate modern methods of applying artificial intelligence to diagnose SARS Cov-2 and predict the development of potential emergencies. Methods The most commonly used electronic databases, such as Scopus and Medline during 2020, were searched. A narrative approach was used to synthesize the extracted data. Results In this review paper, it has been shown that the application of artificial intelligence plays a significant role in virus diagnosis and prognosis in clinical trials. It allows resources to be used much more rationally, such as respirators , in hospitals, during the treatment of SARS Cov-2 and the prediction of possible mortality. The obtained results are from the analysis performed on 120 papers and studies that were electronically taken from papers published on Scopus and Pub Med line. Most commonly used artificial intelligence techniques are convolutional neural networks and machine learning. Conclusions Included studies showed that artificial intelligence can significantly improve the treatment of SARS Cov-2, although many of the proposed methods have not yet been clinically accepted. In addition, more effort is needed to develop standardized reporting protocols or guidelines on applying artificial intelligence into conventional clinical practice. This technology is suitable for fast and accurate diagnosis, prediction and monitoring of current patients and prognosis of disease development in future patients. |
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