A COVID-19 Multipurpose Platform

Towards classification and comprehensive analysis of AI-based COVID-19 diagnostic techniques: A survey

The unpredictable pandemic came to light at the end of December 2019, known as the novel coronavirus, also termed COVID-19, identified by the World Health Organization (WHO). The virus first originated in Wuhan (China) and rapidly affected most of the world's population. This outbreak's impact is experienced worldwide because it causes high mortality risk, many cases, and economic falls. Around the globe, the total number of cases and deaths reported till November 12, 2022, were >600 million and 6.6 million, respectively. During the period of COVID-19, several diverse diagnostic techniques have been proposed. This work presents a systematic review of COVID-19 diagnostic techniques in response to such acts. Initially, these techniques are classified into different categories based on their working principle and detection modalities, i.e. chest X-ray imaging, cough sound or respiratory patterns, RT-PCR, antigen testing, and antibody testing. After that, a comparative analysis is performed to evaluate these techniques' efficacy which may help to determine an optimum solution for a particular scenario. The findings of the proposed work show that Artificial Intelligence plays a vital role in developing COVID-19 diagnostic techniques which support the healthcare system. The related work can be a footprint for all the researchers, available under a single umbrella. Additionally, all the techniques are long-lasting and can be used for future pandemics.

A Survey on harnessing the Applications of Mobile Computing in Healthcare during the COVID-19 Pandemic: Challenges and Solutions

The COVID-19 pandemic ravaged almost every walk of life but it triggered many challenges for the healthcare system, globally. Different cutting-edge technologies such as Internet of things (IoT), machine learning, Virtual Reality (VR), Big data, Blockchain etc. have been adopted to cope with this menace. In this regard, various surveys have been conducted to highlight the importance of these technologies. However, among these technologies, the role of mobile computing is of paramount importance which is not found in the existing literature. Hence, this survey in mainly targeted to highlight the significant role of mobile computing in alleviating the impacts of COVID-19 in healthcare sector. The major applications of mobile computing such as software-based solutions, hardware-based solutions and wireless communication-based support for diagnosis, prevention, self-symptom reporting, contact tracing, social distancing, telemedicine and treatment related to coronavirus are discussed in detailed and comprehensive fashion. A state-of-the-art work is presented to identify the challenges along with possible solutions in adoption of mobile computing with respect to COVID-19 pandemic. Hopefully, this research will help the researchers, policymakers and healthcare professionals to understand the current research gaps and future research directions in this domain. To the best level of our knowledge, this is the first survey of its type to address the COVID-19 pandemic by exploring the holistic contribution of mobile computing technologies in healthcare area.

Innovative Use of a Mobile Web Application to Remotely Monitor Nonhospitalized Patients with COVID-19

Introduction: Most patients with COVID-19 do not require hospitalization but may need close monitoring, which can strain primary care practices. Our objective was to describe the implementation of a mobile web application to monitor COVID-19 signs and symptoms among nonhospitalized primary care patients and to assess the feasibility and acceptability of the application. Study Design: Retrospective analysis of (1) mobile web application data from March through December 2020 and (2) cross-sectional surveys administered in June 2020. Materials and Methods: We enrolled nonhospitalized patients and staff from nine New England primary care practices across 29 sites. Outcomes included feasibility and acceptability of the application as measured by the proportion of texts that resulted in a response, proportion of patients who agreed using the application was easy, and proportion of practice staff who agreed the application reduced outreach burden and that they would recommend use. Results: Five thousand five hundred thirty-two patients used the mobile web application, with 26,466 total responses. Overall, 78% of the daily texts resulted in a response from patients. Most patients agreed that responding to texts was easy (95%) and that they would be willing to participate in other texting programs (78%). Most staff agreed that the program reduced burden of outreach (94%) and that they would recommend use to other practices (100%). Conclusions: Use of a COVID-19 symptom tracking application was feasible and acceptable to patients and primary care practice staff. Outpatient practices should consider use of mobile web applications to monitor nonhospitalized patients with other acute illnesses.