Mobile Apps for COVID-19 Detection and Diagnosis for Future Pandemic Control: Multidimensional Systematic Review.
Mehdi GheisariMustafa GhaderzadehHuxiong LiTania TaamiChristian Fernández-CampusanoHamidreza SadeghsalehiAaqif Afzaal AbbasiPublished in: JMIR mHealth and uHealth (2024)
Mobile apps 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, cloud storage, 5th-generation technology, 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 apps 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 their effects and obtain excellent results in treating patients.
Keyphrases
- data analysis
- deep learning
- systematic review
- coronavirus disease
- sars cov
- loop mediated isothermal amplification
- neural network
- end stage renal disease
- electronic health record
- ejection fraction
- healthcare
- newly diagnosed
- current status
- public health
- chronic kidney disease
- mental health
- big data
- prognostic factors
- machine learning
- randomized controlled trial
- peritoneal dialysis
- risk assessment
- social media
- convolutional neural network
- depressive symptoms
- human health
- psychometric properties