ABSTRACT
The Internet of Medical Things (IoMT) has been applied to provide health care facilities for elders and parents. Remote health care is essential for providing scarce resources and facilities to coronavirus patients. Ongoing IoMT communication is susceptible to potential security attacks. In this research, an artificial intelligence-driven security model of the IoMT is also proposed to simulate and analyses the results. Under the proposed plan, only authorized users will be able to access private and sensitive patient information, and unauthorized users will be unable to access a secure healthcare network. The various phases for implementing artificial intelligence (AI) techniques in the IoMT system have been discussed. AI-driven IoMT is implemented using decision trees, logistic regression, support vector machines (SVM), and k-nearest neighbours (KNN) techniques. The KNN learning models are recommended for IoMT applications due to their low consumption time with high accuracy and effective prediction. © 2023 IEEE.
ABSTRACT
Mucormycosis, which is a life threatening condition, is one of the side effects experienced by post-COVID-19 patients. Early identification and timely treatment are essential to stop the dissemination of the disease, since invasive mucormycosis has a very high fatality rate and significant disease dispersion. Conventional diagnostic techniques, including clinical diagnosis, serology, histopathology and radiology, have limitations in diagnosing the disease at an early stage. This warrants the need for advanced diagnostic tools such as nucleic acid diagnostics, advanced serological tests (ELISpot), PCR (pan-Mucorale test) and multiplex PCR. These techniques have been introduced to identify this invasive fungal infection at an incipient stage, thereby helping clinicians to prevent adverse outcomes. The use of biosensors and micro-needle based diagnostic methodologies will pave the way for devising more point-of-care tests that can be employed for the detection of mucormycosis at an incipient stage. The present review discusses the current techniques available and their drawbacks, and the usefulness of advanced diagnostic tools. Furthermore, the possibility of using future diagnostic methods for the diagnosis of mucormycosis is highlighted.
ABSTRACT
BACKGROUND: The effect of COVID-19 on various facets such as physical, psychological, financial, social, and so on has been investigated extensively. However, the wariness influencing the decision to visit the dentist during this pandemic has received relatively little attention in Indian scenario. The study sought to investigate the general public's anxiety regarding visiting a dentist during the COVID-19 pandemic, including the factors that possibly contribute towards this apprehension among Indian nationals. METHODS: Structured questionnaire based cross sectional observational study. Completed responses were received from 259 individuals. Information was collected on demographic details, medical history, history of COVID-19 infection, history of dental problems, anxiety associated with dental visit and reason for dental visit during the pandemic, whether vaccinated and expecting the dentist to be vaccinated. Apprehension or concerns regarding dental visits were acquired via nine closed-ended questions with dichotomous responses. RESULTS: During the pandemic, 25.9% had dental problems, 24.7% visited the dentist and 81% were anxious about dental visits. 72.6% were concerned about contracting infection from the clinic, 81.5% were concerned about contracting infection in the waiting area, and 87.3% were concerned about whether the clinicians/assistants would meticulously follow standard operating protocols, 88% were concerned about disinfection between patients and 75.7% expressed concern on higher treatment charges due to the pandemic. CONCLUSIONS: The general public is concerned about disease transmission in the dentist's office and increased treatment costs, both of which could have a negative impact on the use of dental services during this COVID-19 pandemic.
Subject(s)
COVID-19 , Anxiety/epidemiology , Cross-Sectional Studies , Humans , Pandemics , PolandABSTRACT
Activity-based learning helps students to learn through participation. A virtual codeathon activity, as part of this learning scheme, was conducted for 180 undergraduate students to focus on analysis and design of solutions to crucial real-world problems in the existing Covid-19 pandemic situation. In this paper, an analysis is made to know the problem solving skills of students given a single problem statement. Evaluators can further collate these multiple solutions into one optimal solution. This Codeathon activity impacts their practical approach towards the analysis and design.
Subject(s)
COVID-19ABSTRACT
To evaluate the psychological impact on ophthalmologists of the COVID 19 crisis during lock-ups in India. An online study was carried out during the lockout on ophthalmologists. The details collected included population information, address, current professional status, form of activity, marital status, effect on training or practises of COVID-19, and effect on income and living cost power. The Patient Health Questionnaire-9 measured psychiatric anxiety. Altogether 2,215 ophthalmologists replied. Multivariable research found that at younger age depression was considerably greater. For an age rise of 1 year, the risks of depression declined by 2.86%. Non-practicing ophthalmologists were more concerned about their schooling or professional development, in particular those with difficulties covering living costs. An extraordinarily significant number of ophthalmologists suffer from psychiatric disorders and will need customised psychological treatment of health.
ABSTRACT
A respiratory disease caused by the corona virus is SARS-CoV-2 spread from China to all over the world. The pathogen causes serious health hazards to humankind from infectious bats. The symptoms range from mild infection to serious problems and life threatening incidence occur globally. The testing method should be more rapid for correct diagnosis and clinical laboratories play a pivotal role in COVID-19 testing, providing presumptive diagnosis at the earliest and nucleic acid based amplification techniques such as RT-qPCR delivering high fidelity reports. The rapid point-of-care testing is crucial in handling such emergency to enhance large-scale surveillance to aid quarantine of suspicious cases and thereby encasing the contagious spread. The review focuses on RT-qPCR and future method such as LAMP assay and nano based techniques are suggested for efficiency and to overcome the false results.