COVID-19 pandemic and the cyberthreat landscape: Research challenges and opportunities.

Although cyber technologies benefit our society, there are also some related cybersecurity risks. For example, cybercriminals may exploit vulnerabilities in people, processes, and technologies during trying times, such as the ongoing COVID-19 pandemic, to identify opportunities that target vulnerable individuals, organizations (e.g., medical facilities), and systems. In this paper, we examine the various cyberthreats associated with the COVID-19 pandemic. We also determine the attack vectors and surfaces of cyberthreats. Finally, we will discuss and analyze the insights and suggestions generated by different cyberattacks against individuals, organizations, and systems.

Trends, Technologies, and Key Challenges in Smart and Connected Healthcare.

Cardio Vascular Diseases (CVD) is the leading cause of death globally and is increasing at an alarming rate, according to the American Heart Association's Heart Attack and Stroke Statistics-2021. This increase has been further exacerbated because of the current coronavirus (COVID-19) pandemic, thereby increasing the pressure on existing healthcare resources. Smart and Connected Health (SCH) is a viable solution for the prevalent healthcare challenges. It can reshape the course of healthcare to be more strategic, preventive, and custom-designed, making it more effective with value-added services. This research endeavors to classify state-of-the-art SCH technologies via a thorough literature review and analysis to comprehensively define SCH features and identify the enabling technology-related challenges in SCH adoption. We also propose an architectural model that captures the technological aspect of the SCH solution, its environment, and its primary involved stakeholders. It serves as a reference model for SCH acceptance and implementation. We reflected the COVID-19 case study illustrating how some countries have tackled the pandemic differently in terms of leveraging the power of different SCH technologies, such as big data, cloud computing, Internet of Things, artificial intelligence, robotics, blockchain, and mobile applications. In combating the pandemic, SCH has been used efficiently at different stages such as disease diagnosis, virus detection, individual monitoring, tracking, controlling, and resource allocation. Furthermore, this review highlights the challenges to SCH acceptance, as well as the potential research directions for better patient-centric healthcare.

Towards an efficient and Energy-Aware mobile big health data architecture.

BACKGROUND AND OBJECTIVES: Mobile and ubiquitous devices are everywhere, generating an exorbitant amount of data. New generations of healthcare systems are using mobile devices to continuously collect large amounts of different types of data from patients with chronic diseases. The challenge with such Mobile Big Data in general, is how to meet the growing performance demands of the mobile resources handling these tasks, while simultaneously minimizing their consumption. METHODS: This research proposes a scalable architecture for processing Mobile Big Data. The architecture is developed around three new algorithms for the effective use of resources in performing mobile data processing and analytics: mobile resources optimization, mobile analytics customization, and mobile offloading. The mobile resources optimization algorithm monitors resources and automatically switches off unused network connections and application services whenever resources are limited. The mobile analytics customization algorithm attempts to save energy by customizing the analytics processes through the implementation of some data-aware schemes. Finally, the mobile offloading algorithm uses some heuristics to intelligently decide whether to process data locally, or delegate it to a cloud back-end server. RESULTS: The three algorithms mentioned above are tested using Android-based mobile devices on real Electroencephalography (EEG) data streams retrieved from sensors and an online data bank. Results show that the three combined algorithms proved their effectiveness in optimizing the resources of mobile devices in handling, processing, and analyzing EEG data. CONCLUSION: We developed an energy-efficient model for Mobile Big Data which addressed key limitations in mobile device processing and analytics and reduced execution time and limited battery resources. This was supported with the development of three new algorithms for the effective use of resources, energy saving, parallel processing and analytics customization.

Realizing telemedicine advantages at the national level: cases from the United Arab Emirates.

This research was initiated to explore telemedicine adoption and diffusion in healthcare organizations in the United Arab Emirates (UAE). Research on telemedicine applications in the UAE focused on two main areas. First, it was revealed that the telemedicine application was not extensively employed in the UAE. There are no self-initiated telemedicine networks or specialty telemedicine centers in the UAE. A study was conducted on the perceptions of UAE healthcare professional concerning their attitudes and behavior toward adopting the telemedicine technology in their organizations, using a theoretical construct extended from the technological innovation literature. Second, existing telemedicine activities were initiated in cooperation with the Mayo Clinic. These consist of multimedia telemedicine systems for second opinion tele-consultations. The effectiveness of this approach has also been examined. The research discusses the findings in the light of the overall literature, highlighting further implications and suggesting ways where telemedicine could be applied in the UAE. There is still much growth and opportunity for self-governed specialty telemedicine systems and networks in the UAE.

Championing telemedicine adoption and utilization in healthcare organizations in New Zealand.

BACKGROUND/OBJECTIVES: This research explored the adoption and the utilisation of telemedicine (TM) in two healthcare organizations (HCOs) in New Zealand (NZ). The research utilised the technological innovation theories, as a guiding theoretical framework, to develop a set of potential determinants which could assist in understanding the adoption and the depth of the TM phenomenon in the two HCOs. METHODOLOGY AND RESULTS: Using case studies design, the findings across the two cases revealed that TM was adopted according to its cost-benefit analysis. Although this approach was found to be important in assessing the adoption of TM, not considering the importance of other factors, highlighted in this research, such as the compatibility and the trialability aspects of the TM technology had a detrimental impact on the success of TM in both cases. CONCLUSION: This research stressed the need for the tight coupling between the roles of both the administrative and the clinical managers in HCOs in order to champion TM adoption and diffusion and to overcome many of the barriers that could hinder telemedicine success in HCOs in NZ. The research points to other implications with respect to the literature and highlights further research in this important area.

Critical success factors for strategic telemedicine planning in New Zealand.

This research reviewed the health information systems (HIS) strategy of the New Zealand government and highlighted different gaps in the strategy, as raised by the different stakeholders involved in this strategy. To address such gaps, the government provided different critical success factors (CSFs) for the successful implementation of the national HIS strategy. The research assessed the strategic importance of telemedicine by highlighting its strengths, weaknesses, opportunities, and threats (SWOT) in health-care organizations. The research utilized the portrayed HIS strategy and CSFs to depict a strategy for telemedicine integration in health-care organizations in New Zealand taking into consideration its SWOT. The developed CSFs are of strategic importance to health-care professionals, researchers, and policymakers interested in integrating telemedicine in health-care delivery at the national level in New Zealand and elsewhere.

Teledermatology: the case of adoption and diffusion of telemedicine health Waikato in New Zealand.

Telemedicine emerged as a possible solution to New Zealand health providers in reaching out to rural patients, by offering medical services and conducting administrative meetings and training. However, despite the rapid growth and high visibility of these projects in countries like the United States, relatively few patients are now being seen through telemedicine. Accordingly, this research attempts to investigate telemedicine's effectiveness in New Zealand by using a theoretical framework. Thus, the purpose of this paper is to explain factors influencing the adoption and diffusion of telemedicine utilising the video conferencing technology (TMVC) for dermatology within Health Waikato Ltd. (HW). Findings indicate weak presence of critical assessment into technological innovation prior to adoption. Factors like complexity, compatibility, and trialability were not assessed extensively by HW, and would have hindered its adoption. Teledermatology was mainly assessed according to its relative advantage and cost effectiveness. While essential this should be alongside other factors pertaining to as addressed within this research. On the other hand, the wide diffusion of teledermatology relied on its economical benefit to HW and on its effectiveness as a diagnostic tool. This research highlights the importance of the product champion for the successful adoption and diffusion of teledermatology.