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Diagnostic tools and automated decision support systems for COVID-19
This chapter explores the primary and auxiliary diagnostic tools for COVID-19 including molecular, serology, and medical imaging-based techniques, and highlights some Artificial Intelligence (AI)-based systems for automated diagnosis. As a molecular testing method, real-time reverse transcription-po...
Autor principal: | |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8084750/ http://dx.doi.org/10.1016/B978-0-323-90959-4.00002-X |
Sumario: | This chapter explores the primary and auxiliary diagnostic tools for COVID-19 including molecular, serology, and medical imaging-based techniques, and highlights some Artificial Intelligence (AI)-based systems for automated diagnosis. As a molecular testing method, real-time reverse transcription-polymerase chain reaction can be used for the qualitative detection of RNA of the pathogen in the specimens of the suspected individuals. This viral RNA identification test is explained with necessary details about the assay procedure, along with its sensitivity to the early diagnosis and some associated challenges regarding the stability of its detection with clinically confirmed cases. On the other hand, serology tests are blood-based tests that are used to identify the exposure of a particular pathogen in the specimen by examining the immune response. For serology-based diagnosis, a general description of different assay procedures, with their uses and benefits, is discussed. Medical imaging is another well-practiced diagnostic technique. Specifically, chest X-ray and CT scan are two popular noninvasive imaging modalities that can be used not only for diagnosis and monitoring of the disease progression but also in confirming the clinical tests and observations, and suggesting treatment and post-hospitalization patient management procedures. The current advancements in AI make the development of computer-aided automated diagnosis (CAD) methods remarkably easier, flexible, and accurate through exploiting all the latest technologies. These methods could utilize the available diagnostic images with clinical features even for early-stage diagnosis. Using such CAD systems can largely expedite the medical image screening process, which subsequently could reduce the burden on the clinicians at the outbreak sites. This chapter discusses the current research efforts for AI-based automated diagnosis system developments, along with analyzing the uses and benefits of these methods. |
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