Development of a Smartphone-Based Expert System for COVID-19 Risk Prediction at Early Stage

Machine learning predictive modeling of the persistence of post-Covid19 disorders: Loss of smell and taste as case studies

The worldwide health crisis triggered by the novel coronavirus (COVID-19) epidemic has resulted in an extensive variety of symptoms in people who have been infected, the most prevalent disorders of which are loss of smell and taste senses. In some patients, these disorders might occasionally last for several months and can strongly affect patients' quality of life. The COVID-19-related loss of taste and smell does not presently have a particular therapy. However, with the help of an early prediction of these disorders, healthcare providers can direct the patients to control these symptoms and prevent complications by following special procedures. The purpose of this research is to develop a machine learning (ML) model that can predict the occurrence and persistence of post-COVID-19-related loss of smell and taste abnormalities. In this study, we used our dataset to describe the symptoms, functioning, and disability of 413 verified COVID-19 patients. In order to prepare accurate classification models, we combined several ML algorithms, including logistic regression, k-nearest neighbors, support vector machine, random forest, extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM). The accuracy of the loss of taste model was 91.5 % with an area-under-cure (AUC) of 0.94, and the accuracy of the loss of smell model was 95 % with an AUC of 0.97. Our proposed modelling framework can be utilized by hospitals experts to assess these post-COVID-19 disorders in the early stages, which supports the development of treatment strategies.

Development and Testing of the Smart Healthcare Prototype System through COVID-19 Patient Innovation

Since the outbreak of the novel coronavirus disease 2019 (COVID-19), the epidemic has gradually slowed down in various countries and people’s lives have gradually returned to normal. To monitor the spread of the epidemic, studies discussing the design of related healthcare information systems have been increasing recently. However, these studies might not consider the aspect of user-centric design when developing healthcare information systems. This study examined these innovative technology applications and rapidly built prototype systems for smart healthcare through a systematic literature review and a study of patient innovation. The design guidelines for the Smart Healthcare System (SHS) were then compiled through an expert review process. This will provide a reference for future research and similar healthcare information system development.

Understanding the Pivotal Role of the Vagus Nerve in Health from Pandemics

The COVID-19 pandemic seems endless with the regular emergence of new variants. Is the SARS-CoV-2 virus particularly evasive to the immune system, or is it merely disrupting communication between the body and the brain, thus pre-empting homeostasis? Retrospective analysis of the COVID-19 and AIDS pandemics, as well as prion disease, emphasizes the pivotal but little-known role of the 10th cranial nerve in health. Considering neuroimmunometabolism from the point of view of the vagus nerve, non-invasive bioengineering solutions aiming at monitoring and stimulating the vagal tone are subsequently discussed as the next optimal and global preventive treatments, far beyond pandemics.