ABSTRACT
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. © 2021 Elsevier Inc. All rights reserved.
ABSTRACT
Timely detection and diagnosis are urgently needed to guide epidemiological measures, infection control, antiviral treatment, and vaccine research. In this review, biomarkers/indicators for diagnosis of coronavirus disease 2019 (COVID-19) or detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the environment are summarized and discussed. It is concluded that the detection methods targeting antibodies are not suitable for screening of early and asymptomatic cases since most patients had an antibody response at about 10 days after onset of symptoms. However, antibody detection methods can be combined with quantitative real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) to significantly improve the sensitivity and specificity of diagnosis, and boost vaccine research. Fast, sensitive and accurate detection methods targeting antigens need to be developed urgently. Various specimens for diagnosis or detection are compared and analyzed. Among them, deep throat saliva and induced sputum are desired for RT-qPCR test or other early detection technologies. Chest computerized tomography (CT) scan, RT-qPCR, lateral flow immunochromatographic strip (LFICS) for diagnosis of COVID-19 are summarized and compared. Specially, potential electrochemical (EC) biosensor, surface enhanced Raman scattering (SERS)-based biosensor, field-effect transistor (FET)-based biosensor, surface plasmon resonance (SPR)-based biosensor and artificial intelligence (AI) assisted diagnosis of COVID-19 are emphasized. Finally, some commercialized portable detection device, current challenges and future directions are discussed.