ABSTRACT
Given that COVID-19 symptoms might be similar to other viral infectious diseases, it becomes difficult to accurately diagnose for COVID-19 without traditional testing strategies like polymerase chain reaction (PCR) testing. As the quarantine and testing requirements have been lifted from most countries, easier and innovative testing strategies are being adopted to maintain high awareness levels in regards to the spread of the disease for both authorities and the public. This paper presents a COVID19 detection strategy that uses Machine Learning (ML) models to accurately diagnose for the disease in patients. The Artificial Intelligence (AI)-enabled solution not only serves the purpose of detecting whether patients are diagnosed with COVID, but also to track their daily symptoms and accurately classify the type of viral disease. Different ML models are trained and tested for accuracy and prediction timings. A decentralized approach is taken for the disease prediction, and hence, blockchain is adapted within the solution to ensure the authenticity of the user data. The solution has been implemented to allow users to receive real-time disease diagnosis using a web-based interface.
ABSTRACT
The fourth industrial revolution (Industry 4.0) has prompted new and innovative solutions that are reliant on Artificial Intelligence (AI) and contemporary technological advancements. Secure, intelligent, and on-demand healthcare services for patients is one of the core pillars of Industry 4.0. Patient medical data security and privacy is a crucial part of electronic healthcare systems. Disease diagnosis and treatment are highly dependent on the authenticity and security of patient data, both when stored and communicated. Blockchain technology plays a vital role in transaction authentication and secure decentralized immutable data storage. With that said, in this paper, we present an interactive healthcare information system that enables COVID-19 contact tracing and vaccine certificate validation for users. The solution uses a blockchain technique to validate the certificates. The implementation and evaluation details of the system are presented together with result findings.
ABSTRACT
The COVID-19 pandemic, which spread rapidly in late 2019, has revealed that the use of computing and communication technologies provides significant aid in preventing, controlling, and combating infectious diseases. With the ongoing research in next-generation networking (NGN), the use of secure and reliable communication and networking is of utmost importance when dealing with users' health records and other sensitive information. Through the adaptation of artificial-intelligence-enabled NGN, the shape of healthcare systems can be altered to achieve smart and secure healthcare capable of coping with epidemics that may emerge at any given moment. In this article, we envision a cooperative and distributed healthcare framework that relies on state-of-the-art computing, communication, and intelligence capabilities, namely, federated learning, mobile edge computing, and blockchain, to enable epidemic (or suspicious infectious disease) discovery, remote monitoring, and fast health authority response. The introduced framework can also enable secure medical data exchange at the edge and between different health entities. This technique, coupled with the low latency and high bandwidth functionality of 5G and beyond networks, would enable mass surveillance, monitoring, and analysis to occur at the edge. Challenges, issues, and design guidelines are also discussed in this article with highlights on some trending solutions.