ABSTRACT
In medical applications, embedded system technologies have become increasingly significant. Developing tools to improve the safety of healthcare professionals in the occurrence of epidemic contagious diseases, such as pandemic influenza, is a top priority. There has been an increase in demand for telemedicine services in recent years due to the rise in infectious diseases such as the Covid-19 viral infection. Telemedicine services include diagnostic tests, prognosis, and patient monitoring. Various heartbeat monitoring systems have been introduced to mitigate human distractions and explore the things that happen inside the human body. The cardiovascular system pushes blood and transports oxygen and nutrients via blood circulation. Heartbeat monitoring plays a vital role in preventing real-time accidents and providing the status of the heart's pumping prior to the external world. This review starts by using various sensors that measure the heart rate in a sophisticated manner, including invasive and non-invasive technologies. The amendable support with this modern device is retrofitted with the environmental conditions to provide the information rate without any delay. Nowadays, the emerging wireless sensor devices simplify collecting data regarding heart rate monitoring and sharing the information with anyone who resides in any part of the world. The types of sensors and the practical difficulties that various monitoring system faces are reviewed in detail. © 2022 River Publishers.
ABSTRACT
Purpose: For the first time in a decade, a new form of pneumonia virus, coronavirus, COVID-19, appeared in Wuhan, China. To date, it has affected millions of people, killed thousands and resulted in thousands of deaths around the world. To stop the spread of this virus, isolate the infected people. Computed tomography (CT) imaging is very accurate in revealing the details of the lungs and allows oncologists to detect COVID. However, the analysis of CT scans, which can include hundreds of images, may cause delays in hospitals. The use of artificial intelligence (AI) in radiology could help to COVID-19-positive cancer in this manner is the main purpose of the work. Design/methodology/approach: CT scans are a medical imaging procedure that gives a three-dimensional (3D) representation of the lungs for clinical purposes. The volumetric 3D data sets can be regarded as axial, coronal and transverse data sets. By using AI, we can diagnose the virus presence. Findings: The paper discusses the use of an AI for COVID-19, and CT classification issue and vaccination details of COVID-19 have been detailed in this paper. Originality/value: Originality of the work is, all the data can be collected genuinely and did research work doneown methodology. © 2021, Emerald Publishing Limited.
ABSTRACT
According to the first SARS-CoV-2 pandemic reports that signs and symptoms were identified less commonly among pediatric patients than adults. The multisystem inflammatory syndrome in children (MISC), which is linked to COVID -19, was first identified in April. Fever, presented in two or more organ systems at the same time, altered inflammatory criteria, and experimental or epidemiological proof of SARSCoV-2 infection are all symptoms of MIS-C. Kawasaki disorder, toxic shock syndrome, and secondary hemophagocytic lymph histiocytosis syndrome/macrophage activation syndrome all have certain clinical elements in common with MIS-C. The clinical features of seven cases of MIS-C handled in the Republic of Moldova are described in this study.