Mobile applications in COVID-19 detection and diagnosis: an efficient tool to control the future pandemic; a multidimensional systematic review of the state of the art.

Researchers

Journal

Modalities

Models

Abstract

Background: In the modern world, mobile applications are essential for human advancement, and pandemic control is no exception. The use of mobile applications and technology for the detection and diagnosis of COVID-19 disease has been the subject of numerous investigations.Objective: Since no thorough analysis of COVID-19 epidemic prevention has been done using mobile applications. Due to this gap, the current study provides comprehensive information regarding the different fields of mobile applications in diagnosing COVID-19 diseases in the pandemic era, intending to help software companies and clinical researchers.Methods: In this systematic review, 535 studies were discovered after searching five major research databases (ScienceDirect, Scopus, PubMed, Web of Science, and IEEE). Of these studies, only 42 were chosen after applying inclusion and exclusion criteria using the PRISMA protocol concerned with diagnosing and detecting COVID-19.Results: Mobile applications can be categorized into five areas based on the content of these studies: contact tracing, data gathering, data visualization, artificial intelligence-based diagnosis, rule- and guideline-based diagnosis, and data transformation. Patients with COVID-19 have been identified using mobile applications employing a variety of clinical, geographic, demographic, radiological, serological, and laboratory data. Most studies concentrated on using artificial intelligence (AI) methods to identify people who might have COVID-19. Additionally, symptoms, cough sounds, and radiological images were used more frequently compared to other data types. Deep learning techniques, such as CNN, performed comparatively better in the processing of healthcare data than other types of AI techniques, which improved the diagnosis of COVID-19.Conclusions: Mobile applications could soon play a significant role as a powerful tool for data collection, epidemic health data analysis, and the early identification of suspected cases. These technologies can work with the Internet of Things (IoT), cloud storage, 5G, and cloud computing. Processing pipelines can be moved to mobile device processing cores using new deep learning methods, such as lightweight neural networks. In the event of future pandemics, mobile applications will play a critical role in rapid diagnosis using various image data and clinical symptoms. Consequently, the rapid diagnosis of these diseases can improve the management of the disease’s effects and bring excellent results in treating patients.