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Putative role of multi-omics technologies in the investigation of persistent effects of COVID-19 on vital human organs
Published in Sanjeeva Srivastava, Multi-Pronged Omics Technologies to Understand COVID-19, 2022
Susmita Ghosh, Akanksha Salkar, Firuza Parikh
Currently, reverse transcription-polymerase chain reaction (RT-PCR) is the most commonly used method for diagnosing COVID-19 infection. Although many rapid antigen tests are available commercially, they are auxiliary to the RT-PCR test. Imaging modalities such as chest radiography, pulmonary US, chest CT, and angiography are also used to diagnose COVID-19 supplementary to the RT-PCR test. Moreover, chest CT has been used to predict the prognosis of COVID-19 (Feng et al. 2020). Furthermore, a significant number of recovered patients may still have some impairment. There is enough evidence regarding the multi-organ involvement of COVID-19. However, the long-term prevalence of these complications is not well studied. With the current number of people who have been affected by COVID-19, the sudden surge in post-COVID-19 illnesses in recovered people may overwhelm the medical system. Therefore, monitoring these patients becomes necessary to prevent such diseases or to facilitate their prognosis (Balachandar et al. 2020). Thus, in this chapter, we review various complications of COVID-19 in different vital organs, probable long-term effects, and the role of omics technology.
Tapping the Big Data Analytics and IoT in the Pandemic Era
Published in Chinmay Chakraborty, Digital Health Transformation with Blockchain and Artificial Intelligence, 2022
Yashikha Dhiman, Ashish Joshi, Isha Pant
Computed tomography and X-rays are common diagnostic and therapeutic tools in diagnostic imaging. CT scans and X-ray imaging were essential for determining the SARS-COV-2 infection during the COVID-19 epidemic. Disease type classification enabled by AI will aid in the automated processes of the screening procedure, lowering the period of time clinicians and patients must engage. As a consequence, it safeguards medical imaging professionals while also aiding in viral transmission. To assess the concentration of any type of RNA, the Reverse Transcription-Polymerase Chain Reaction (RT-PCR) assay is widely employed. COVID-19 infection is diagnosed with this RT-PCR. The RT-PCR test, on the other hand, has certain flaws. The most sophisticated Artificial Intelligence-powered technologies and techniques will undoubtedly aid in the establishment of resilience against the COVID-19 pandemic. The identification technique was utilized on CT scans of the abdomen in a study that showed rapid recognition of COVID-19 using machine learning approaches. Qualified radiologists found that COVID-19 was different from other viral pneumonias based on CT scans. As a consequence, medical practitioners will be able to diagnose COVD-19 infection early on.
Rapid Detection of COVID-19 Using FET and MOSFET Biosensors
Published in Suman Lata Tripathi, Kanav Dhir, Deepika Ghai, Shashikant Patil, Health Informatics and Technological Solutions for Coronavirus (COVID-19), 2021
For rising pathogens, RT-PCR (real-time reverse transcription–polymerase chain reaction) is the essential method of determination. As of now, real-time RT-PCR is utilized for the recognition of critical respiratory syndrome, SARS-CoV-2, dependent on the latest distributed research center conventions [6]. SARS-CoV-2 is profoundly contagious and is as of now expanding quickly over the globe. The pace of transmission of COVID-19 is a lot quicker than those of Middle East respiratory Syndrome (MERS) and severe acute respiratory syndrome (SARS). Additionally, the transmission of asymptomatic COVID-19 has been accounted for [7,8]. Molecular findings utilizing ongoing RT-PCR take in any event 3 hours, including planning of the viral RNA. What is more, the step of RNA planning can influence analytic precision, henceforth, profoundly delicate immunological indicative strategies that straightforwardly distinguish viral antigens in the clinical samples. Test planning initiatives are fundamental for quick and exact analysis of corona virus. Among the numerous analytic techniques as of now accessible, biosensing gadgets which are based on FETs offer numerous benefits. In addition to the capacity to build profoundly responsive and prompt estimations utilizing limited quantities of analytes, biosensors based on FETs are found to be potentially useful in onsite detection and clinical diagnosis [9,10]. Graphene is the two-dimensional sheet in which atoms of carbon are arranged hexagonally, and all are uncovered on its surface [11]. It has demonstrated to be a helpful material for different detecting stages because of its unprecedented features that include high conductivity of electrons, greater mobility of carriers and huge area [12]. FET biosensors made up of graphene can recognize encompassing changes on its surface and give an ideal detecting condition to low-noise and ultrasensitive detection. Considering this, biosensing technology based on FET based with graphene is exceptionally alluring for uses identified with sensitive or responsive immunological findings [13,14].
DNN based approach to classify Covid’19 using convolutional neural network and transfer learning
Published in International Journal of Computers and Applications, 2022
Bhavya Joshi, Akhilesh Kumar Sharma, Narendra Singh Yadav, Shamik Tiwari
Covid-19 is detected in a patient through two widely used tests. One is the highly accurate Reverse Transcription Polymerase Chain Reaction (RT–PCR). This test has an excellent accuracy rate and is able to detect even a small amount of the virus. However, this is highly complicated and time consuming, giving a result in multiple days. The other test is the Rapid Antigen test, which gives highly inaccurate results with a failure rate of 40–50% [4]. Due to the lack of adequate testing facilities, the virus has the potential to spread unchecked. This has led to the need for alternate methods of testing which are fast and inexpensive. A probable approach is analyzing radiography images to detect the presence of the virus. Numerous studies have shown that the viruses of this family can be detected from their manifestation in X-Ray images [5–7].
Gold nanoparticles as radiosensitizer for radiotherapy and diagnosis of COVID-19: A review
Published in Nanoscale and Microscale Thermophysical Engineering, 2022
Abdul Khaliq Mokhtar, Norsyahidah Mohd Hidzir, Faizal Mohamed, Irman Abdul Rahman, Syazwani Mohd Fadzil, Afifah Mardhiah Mohamed Radzi, Nur Ain Mohd Radzali
The reverse transcription-polymerase chain reaction (RT-PCR) test in molecular testing category is currently the litmus test for pathogen detection, in this case, COVID-19 outbreak [178]. However, RT-PCR possesses a few drawbacks, which include false negatives, existence of asymptomatic carriers, complexity, and concerns associated with its replication, responsiveness, and precision [179, 180]. In addition, there is a lack of RT-PCR kits and insufficient medical personnel to operate and perform testing in numerous developing countries, which raises concerns and burdens for them to adopt RT-PCR testing [181]. Some people may also feel uncomfortable, particularly children, as deep nasal swabs are required. Thus, recent advancements and approaches in nanotechnology-based pathogen detection methods have paved the way for more appropriate and simpler options for detecting pathogens in faster and efficient manners [182, 183]. Table 3 shows the diagnostic of coronavirus by AuNP-based approach. As regards enhancing the performance of detecting virus, AuNP has been used in various virus detection systems such as the colloidal gold immunochromatography assay (GICA) [188, 193], reverse transcription loop-mediated isothermal amplification (RT-LAMP) [194, 195], enzyme-linked immunosorbent assay (ELISA) [188, 196], and lateral flow [186, 197] due to its ultrasmall size and large surface area.