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In view of the elderly caregiving service being in high demand nowadays, the purpose of this paper is to develop an intelligent e-healthcare system for the domestic care industry by using the Internet of Things (IoTs) and Fuzzy Association Rule Mining (FARM) approach.

The IoTs connected with the e-healthcare system collect real-time vital sign monitoring data for the e-healthcare system. The FARM approach helps to identify the hidden relationships between the data records in the e-healthcare system to support the elderly care management tasks.

To evaluate the proposed system and approach, a case study was carried out to identify the association between the specific collected demographic data, behavior data and the health measurements data in the e-healthcare system. It is found that the discovered rules are useful for the care management tasks in the elderly healthcare service.

Knowledge discovery in databases uses various data mining techniques and rule-based artificial intelligence algorithms. This paper demonstrates complete processes on how an e-healthcare system connected with IoTs can support the elderly care services via a data collection phase, data analysis phase and data reporting phase by using the FARM to evaluate the fuzzy sets of the data attributes. The caregivers can use the discovered rules for proactive decision support of healthcare services and to improve the overall service quality by enhancing the elderly healthcare service responsiveness.

Healthcare is among the fastest‐growing sectors in both developed and emerging economies. E‐healthcare is contributing to the explosive growth within this industry by utilizing the internet and all its capabilities to support its stakeholders with information searches and communication processes. The purpose of this paper is to present the state‐of‐the‐art and to identify key themes in research on e‐healthcare.

A review of the literature in the marketing and management of e‐healthcare was conducted to determine the major themes pertinent to e‐healthcare research as well as the commonalities and differences within these themes.

Based on the literature review, the five major themes of e‐healthcare research identified are: cost savings; virtual networking; electronic medical records; source credibility and privacy concerns; and physician‐patient relationships.

Based on these major themes, managerial implications for e‐healthcare are formulated. Suggestions are offered to facilitate healthcare service organizations' attempts to further implement and properly utilize e‐healthcare in their facilities. These propositions will also help these stakeholders develop and streamline their e‐healthcare processes already in use. E‐healthcare systems enable firms to improve efficiency, to reduce costs, and to facilitate the coordination of care across multiple facilities.

Use of technology for quality healthcare services has developed into a new field known as “e-Healthcare services.” Healthcare providers often judge their quality of services with consumer satisfaction. With e-Healthcare services, consumer satisfaction is influenced by the quality of healthcare services provided and the demographic characteristics. The purpose of the present case study is to recognize the important predictors of quality, which are significant for consumer satisfaction with e-Healthcare services by using Zineldin's 5Qs model. It also aims to find the strength of association among the predictors of consumer satisfaction and the demographic characteristics of the respondents.

A questionnaire-based study was conducted at a public (PGIMER, Chandigarh) and a private hospital (Fortis Hospital, Mohali) of Punjab, India, from February 2018 to March 2019. The structured, closed-ended questionnaire, to be marked on a 1–5 point Likert scale, was adapted from Zineldin's 5Qs model and was distributed to the respondents sitting in the waiting halls of the selected hospitals. The respondents comprised of both the patients and their attendants who were aware of e-Healthcare services and were using them.

The analysis identified quality of interaction, quality of hospital atmosphere and quality of object to be the key predictors of consumer satisfaction with e-Healthcare services. The results reveal a strong association between different demographic characteristics and overall consumer satisfaction with e-Healthcare services.

The results suggest that improvements in the quality of interaction, quality of hospital atmosphere and quality of object may result in higher consumer satisfaction with e-Healthcare services. Working on the identified dimensions of quality will help the e-Healthcare providers in identifying functional problems of e-Healthcare services and developing improvement strategies, which will also result in better health and quality outcomes. The results of this study will help the e-Healthcare providers in better segmentation of e-Healthcare consumers based on their demographic characteristics and in developing better marketing strategies.

This paper focuses on the quality of e-Healthcare services only and attempts to identify the quality dimensions, which leads to the satisfaction of e-Healthcare consumers. The identified quality dimensions will help in designing better e-Healthcare services and framing policies. It also highlights the association of demographic characteristics with important quality dimensions.

This study explores privacy challenges in recommender systems (RSs) and how they have leveraged privacy-preserving technology for risk mitigation. The study also elucidates the extent of adopting privacy-preserving RSs and postulates the future direction of research in RS security.

The study gathered articles from well-known databases such as SCOPUS, Web of Science and Google scholar. A systematic literature review using PRISMA was carried out on the 41 papers that are shortlisted for study. Two research questions were framed to carry out the review.

It is evident from this study that privacy issues in the RS have been addressed with various techniques. However, many more challenges are expected while leveraging technology advancements for fine-tuning recommenders, and a research agenda has been devised by postulating future directions.

The study unveils a new comprehensive perspective regarding privacy preservation in recommenders. There is no promising study found that gathers techniques used for privacy protection. The study summarizes the research agenda, and it will be a good reference article for those who develop privacy-preserving RSs.

The purpose of this paper is to explore the route map for employing efficient e‐governance so that at least existing resource and infrastructure are better utilized and deficiencies are tracked for future planning. National health is one of the most important factors in a country's economic growth. India seems to be a victim of the vicious cycle around poor economy and poor health conditions.

A detailed study was carried out to find out India's healthcare infrastructure and its standing in e‐governance initiatives. After consolidating the fact that effective e‐governance can enhance the quality of healthcare service even within limited resources, authors explored success and failure factors of many e‐governance initiatives in India and abroad. Finally, an e‐governance framework is suggested based on the above factors together with the authors' own experience of implementing e‐governance projects in India and abroad.

The suggested framework is based on a phased implementation approach. The first phase “Information Dissemination” is more geared towards breaking the “digital divide” across three dimensions: G2Business; G2Citizen; and G2Agent. The most advanced stage is aimed towards joining up healthcare information across the above three dimensions and drawing meaningful analytics out of it. The recommendations also include management of Policies, Scope, Process Reform, Infrastructure, Technology, Finance, Partnership and People for efficient implementation of such e‐governance initiatives.

The paper provides measures for continuous evaluation of systems as one passes through various stages of implementation. However, the framework can be tested on real or simulated environment to prove its worthiness.

This paper can be a potential frame of reference for nation‐wide e‐healthcare projects not only in India but also in other developing countries. The paper also describes challenges that are most likely to be faced during implementation.

Since the paper is practical in nature, the real appeal will be to practitioners who are responsible for implementation of large e‐governance initiatives for improving healthcare services.

Empowered patients are allies to the healthcare system, especially in emergency situations. Social media use has emerged to be a major means by which patients interact with the healthcare system, and in times such as the current COVID-19 situation social media has to play an even greater crisis management role by empowering patients. Social media channels serve numerous beneficial purposes, despite them also being blamed for the spread of misinformation during this crisis. In this Gulf Cooperation Council (GCC) focused case study, we will discuss the increasingly greater role being played by the social media in healthcare in the region and how that empowers not just the patients but the system as a whole. In the GCC region, the healthcare sector is found to reflect a steady growth, leading to an increased drive for empowering patients by lowering the barriers to effective communication and consultation through online media. As of today, social media has become an element of the telehealth infrastructure being deployed in the region. During COVID-19, patients are seen to leverage it pointedly for online health consultations thereby lowering the stress on the healthcare system and adding to efficiencies.

The purpose of this study is to alleviate the specified issues to a great extent. To promote patients’ health via early prediction of diseases, knowledge extraction using data mining approaches shows an integral part of e-health system. However, medical databases are highly imbalanced, voluminous, conflicting and complex in nature, and these can lead to erroneous diagnosis of diseases (i.e. detecting class-values of diseases). In literature, numerous standard disease decision support system (DDSS) have been proposed, but most of them are disease specific. Also, they usually suffer from several drawbacks like lack of understandability, incapability of operating rare cases, inefficiency in making quick and correct decision, etc.

Addressing the limitations of the existing systems, the present research introduces a two-step framework for designing a DDSS, in which the first step (data-level optimization) deals in identifying an optimal data-partition (Popt) for each disease data set and then the best training set for Popt in parallel manner. On the other hand, the second step explores a generic predictive model (integrating C4.5 and PRISM learners) over the discovered information for effective diagnosis of disease. The designed model is a generic one (i.e. not disease specific).

The empirical results (in terms of top three measures, namely, accuracy, true positive rate and false positive rate) obtained over 14 benchmark medical data sets (collected from https://archive.ics.uci.edu/ml) demonstrate that the hybrid model outperforms the base learners in almost all cases for initial diagnosis of the diseases. After all, the proposed DDSS may work as an e-doctor to detect diseases.

The model designed in this study is original, and the necessary parallelized methods are implemented in C on Cluster HPC machine (FUJITSU) with total 256 cores (under one Master node).

The purpose of this paper is to examine the introduction of self‐service technology (SST) in health diagnosis as a means to reduce costs and improve quality in the health care sector – at the same time.

A survey with an internet‐based medical self‐diagnosis application as the focal technology is conducted. The research hypotheses are tested by using a scenario and questionnaire approach, in which respondents prior to responding read a scenario.

To test the hypotheses, structural equation modeling using LISREL was performed. It was found that the Technology Acceptance Model (TAM) for users, described according to the Technology Readiness Index (TRI) as pioneers, has a very good ability to predict future behavioral intent. TAM has an excellent capability to predict future behavioral intent of this new application in this new context, i.e. health care services.

The paper only tests TAM for a given population described as pioneers. Future research should test for other categories of users, as this may impact different drivers of behavioral intent/adoption in the TAM.

For policy makers (e.g. politicians), this study has great implications as it documents a methodology of testing a population's receptiveness to new technology – technology that can greatly improve quality, costs and satisfaction issues with government services and reduce risk when implementing the new service.

In the context of increased healthcare spending and possibly unsustainable healthcare‐funding models, the current research investigated people's readiness and attitude toward performing self‐diagnosis which may offer a patient‐centered access to health services. To the best of the authors' knowledge, this has never been done before.

The growing implementation of electronic health (e-health) systems has raised the importance of analyzing how these systems have been implemented in diverse regions. By employing a contextual sensitive approach and social mechanism theory, this study aims to better understand the reasons for the success and failure of e-health initiatives in the ex-Yugoslav region and derive useful insights for policymakers.

We employ a narrative review process grounded in the social mechanism theory, extended with field experts’ review, to acquire state-of-the-art information.

Findings indicate that different e-health systems coexist and evolve in different contexts in different countries, with varying levels of success. The contextual differences shape the broader environment, affecting the level of preparedness and capability for e-health implementation. Top-down approaches dominate e-health implementation in most countries when it comes to design process features, and more developed countries do not rely on strong social mechanisms for implementing e-health due to the openness of their culture towards e-health innovations.

Analyzing the milestones, challenges and functionalities of e-health systems in the region of interest can assist policymakers, academics and practitioners in making informed decisions and recommendations to enhance future e-health implementation.

No known studies evaluated e-health initiatives in the former ex-Yugoslav countries holistically and evolutionarily in the form of a comprehensive regional study. Further, our research endeavor is contextually specific since the health systems of these countries in the past were tied together under the federative umbrella health system and then diverged in terms of e-health development.