Machine learning empowered COVID-19 patient monitoring using non-contact sensing:An extensive review / 药物分析学报

The severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),which caused the coronavirus disease 2019(COVID-19)pandemic,has affected more than 400 million people worldwide.With the recent rise of new Delta and Omicron variants,the efficacy of the vaccines has become an important question.The goal of various studies has been to limit the spread of the virus by utilizing wireless sensing technologies to prevent human-to-human interactions,particularly for healthcare workers.In this paper,we discuss the current literature on invasive/contact and non-invasive/non-contact technologies(including Wi-Fi,radar,and software-defined radio)that have been effectively used to detect,diagnose,and monitor human activities and COVID-19 related symptoms,such as irregular respiration.In addition,we focused on cutting-edge machine learning algorithms(such as generative adversarial networks,random forest,multilayer perceptron,support vector machine,extremely randomized trees,and k-nearest neighbors)and their essential role in intelligent healthcare systems.Furthermore,this study highlights the limitations related to non-invasive techniques and prospective research directions.

Incidence of methicillin resistant Staphylococcus aureus in Peshawar

There is considerable variation in the percentage of isolates of methicillin resistant Staphylococcus aureus [MRSA]. There are several mechanisms for methicillin resistance. The most important is low affinity of penicillin binding proteins for beta-lactam antibiotics. The objectives of this study were to establish the pattern of MRSA incidence in Peshawar in recent years, and to identify high risk groups for acquiring infection amongst the city population. All positive MRSA cases reported at city laboratory were employed in the study. These were recorded over the time period elapsing from 2009 to 2011. For each patient, records were looked at for age, sex, specimen tested positive, hospital/community acquired and if hospital acquired then which particular hospital within the city was infection contracted at. Also patient records were addressed for any immune system abnormalities, any operation conducted, presence or absence of diabetes and any history of intravenous drug use. There were a total of 929 MRSA cases in our study, of which 538 were males and 391 were females. MRSA frequency for the year 2009 was 207, for 2010 it was 284 and for 2011 it was 438. The frequency of MRSA increased by 54% from the year 2009 to 2011. A potentially alarming increase in MRSA incidence within the city has been observed in recent years threatening to rise further judging the current trend. Those at a high risk of contracting infection include males aged between 20-29 years, hospitalised, diabetics, immune system compromised, and individuals with a history of IV drug use