Towards emotive sensory Web in virtual health care: Trends, technologies, challenges and ethical issues

From static web to metaverse: reinventing medical education in the post-pandemic era

The World Wide Web and the advancement of computer technology in the 1960s and 1990s respectively set the ground for a substantial and simultaneous change in many facets of our life, including medicine, health care, and medical education. The traditional didactic approach has shifted towards more dynamic and interactive methods, leveraging technologies such as simulation tools, virtual reality, and online platforms. At the forefront is the remarkable evolution that has revolutionized how medical knowledge is accessed, disseminated, and integrated into pedagogical practices. The COVID-19 pandemic also led to rapid and large-scale adoption of e-learning and digital resources in medical education because of widespread lockdowns, social distancing measures, and the closure of medical schools and healthcare training programs. This review paper examines the evolution of medical education from the Flexnerian era to the modern digital age, closely examining the influence of the evolving WWW and its shift from Education 1.0 to Education 4.0. This evolution has been further accentuated by the transition from the static landscapes of Web 2D to the immersive realms of Web 3D, especially considering the growing notion of the metaverse. The application of the metaverse is an interconnected, virtual shared space that includes virtual reality (VR), augmented reality (AR), and mixed reality (MR) to create a fertile ground for simulation-based training, collaborative learning, and experiential skill acquisition for competency development. This review includes the multifaceted applications of the metaverse in medical education, outlining both its benefits and challenges. Through insightful case studies and examples, it highlights the innovative potential of the metaverse as a platform for immersive learning experiences. Moreover, the review addresses the role of emerging technologies in shaping the post-pandemic future of medical education, ultimately culminating in a series of recommendations tailored for medical institutions aiming to successfully capitalize on revolutionary changes.

The applications of machine learning techniques in medical data processing based on distributed computing and the Internet of Things

Medical data processing has grown into a prominent topic in the latest decades with the primary goal of maintaining patient data via new information technologies, including the Internet of Things (IoT) and sensor technologies, which generate patient indexes in hospital data networks. Innovations like distributed computing, Machine Learning (ML), blockchain, chatbots, wearables, and pattern recognition can adequately enable the collection and processing of medical data for decision-making in the healthcare era. Particularly, to assist experts in the disease diagnostic process, distributed computing is beneficial by digesting huge volumes of data swiftly and producing personalized smart suggestions. On the other side, the current globe is confronting an outbreak of COVID-19, so an early diagnosis technique is crucial to lowering the fatality rate. ML systems are beneficial in aiding radiologists in examining the incredible amount of medical images. Nevertheless, they demand a huge quantity of training data that must be unified for processing. Hence, developing Deep Learning (DL) confronts multiple issues, such as conventional data collection, quality assurance, knowledge exchange, privacy preservation, administrative laws, and ethical considerations. In this research, we intend to convey an inclusive analysis of the most recent studies in distributed computing platform applications based on five categorized platforms, including cloud computing, edge, fog, IoT, and hybrid platforms. So, we evaluated 27 articles regarding the usage of the proposed framework, deployed methods, and applications, noting the advantages, drawbacks, and the applied dataset and screening the security mechanism and the presence of the Transfer Learning (TL) method. As a result, it was proved that most recent research (about 43%) used the IoT platform as the environment for the proposed architecture, and most of the studies (about 46%) were done in 2021. In addition, the most popular utilized DL algorithm was the Convolutional Neural Network (CNN), with a percentage of 19.4%. Hence, despite how technology changes, delivering appropriate therapy for patients is the primary aim of healthcare-associated departments. Therefore, further studies are recommended to develop more functional architectures based on DL and distributed environments and better evaluate the present healthcare data analysis models.

Potential ethical problems in the creation of open educational resources through virtual spaces in academia

The concept of open educational resources (OER) is an emerging phenomenon that encourages modern teaching and learning in the higher education sector. Although many institutions are promoting the adoption and creation of OER, they are still lacking in the policies and development guidelines related to the creation. This could perpetrate the potential ethical problems that affect the development of OER. This study aimed to find out ethical procedures and peer-review processes associated with the adoption and development of OER. A qualitative approach was used to gather data from OER developers in the academic space. Structuration theory was considered the main theoretical underpinning of this study. The commonly used big data virtual spaces for OER, such as social media and learning management systems (LMS), were identified. The study articulates three major causalities of OER's ethical problems, as follows: non-compliance to openness, transactional purchases of OER, non-incentives for developers. Also, the scholars' ideas and OER outputs cannot be undermined; however, there is a need for a peer-review process in the creation of OER. Institutions are expected to formulate the standards and requirements to be followed in the creation of OER because OER contributes to the rising of big data in the education domains. The study recommends that OER be developed for a specific purpose and aligned with the specific subject content, and the resource must be precise and peer reviewed for quality measures.

Are we there yet? Unbundling the potential adoption and integration of telemedicine to improve virtual healthcare services in African health systems

Since the outbreak of COVID-19, the attention has now shifted towards universal vaccination to gracefully lift strict COVID-19 restrictions previously imposed to contain the spread of the disease. Sub-Saharan Africa is experiencing an exponential increase of infections and deaths coupled with vaccines shortages, personal protective equipment, weak health systems and COVID-19 emerging variants. Some developed countries integrated telemedicine to reduce the impacts of the shortage of healthcare professionals and potentially reduce the risk of exposure, ensuring easy delivery of quality health services while limiting regular physical contact and direct hospitalization. However, the adoption of telemedicine and telehealth is still nascent in many sub-Saharan Africa countries. Therefore, this study reflects on progress made towards the use of telemedicine, virtual health care services, challenges encountered, and proffers ways to address them. We conducted a systematic literature review to synthesise literature on telemedicine in sub-Saharan Africa. The study revealed that telemedicine provides unprecedented benefits such as improving efficiency, effective utilization of healthcare resources, forward triaging, prevention of medical personnel infection, aiding medical students' clinical observation and participation, and assurance of social support for patients. However, the absence of policy on virtual care and political will, cost of sustenance of virtual health care services, inadequate funding, technological and infrastructural barriers, patient and healthcare personnel bias on virtual care and cultural barriers are identified as limiting factors to the adoption of virtual health care in many African health systems. To alleviate some of these barriers, we recommend the development of robust policies and frameworks for virtual health care, the inclusion of virtual care in the medical school curriculum, supporting virtual care research and development, increasing health funding, removing monopolisation of telecommunication services, developing of virtual health solutions that address eccentricities of African health systems.