E-healthcare Services Research Articles

Securing E-Healthcare Images Using an Efficient Image Encryption Model

With the advancements in e-healthcare services, it is possible to provide remote medical services to patients and swifter first aid. Medical images play an essential role in e-healthcare applications for providing quick and better remote diagnosis and treatment to patients. Medical images generally comprise secret details about the patients and are therefore prone to various security threats during their transmission over public networks. Thus, it is required to secure these images prior to their communication over public networks. But due to distinctive properties of medical images, like higher correlation and redundancy among the pixels, and larger size, it is required to design an efficient encryption model to resist against various security threats. In this paper, an efficient encryption model for medical images is proposed. To obtain the secret keys, six-dimensional hyperchaotic map (SDHM) is proposed. Firstly, plain medical image is divided into three channels such as red, green, and blue. Secret keys are used to diffuse these channels. Lastly, encrypted channels are concatenated and final encrypted medical image is obtained. Extensive experiments are drawn by considering the benchmark medical images. Also, comparisons are performed among the proposed SDHM and competitive techniques by considering various performance metrics. Comparative analysis reveals that the proposed SDHM achieves remarkably good performance than the existing encryption models.

Analysis of E-mental health research: mapping the relationship between information technology and mental healthcare

BackgroundE-mental healthcare is the convergence of digital technologies with mental health services. It has been developed to fill a gap in healthcare for people who need mental wellbeing support that may not otherwise receive psychological treatment. With an increasing number of e-mental healthcare and research, this study aimed to investigate the trends of an e-mental health research field that integrates interdisciplinary fields and to examine the information technologies is being used in mental healthcare. To achieve the research objectives, bibliometric analysis, information extraction, and network analysis were applied to analyze e-mental health research data.MethodsE-mental health research data were obtained from 3663 bibliographic records from the Web of Science (WoS) and 3172 full-text articles from PubMed Central (PMC). The text mining techniques used for this study included bibliometric analysis, information extraction, and visualization.ResultsThe e-mental health research topic trends primarily involved e-health care services and medical informatics research. The clusters of research comprised 16 clusters, which refer to mental sickness, e-health, diseases, information technology (IT), and self-management. The information extraction analysis revealed a triple relation with IT and biomedical domains. Betweenness centrality was used as a measure of network graph centrality, based on the shortest path to rank the important entities and triple relation; nodes with higher betweenness centrality had greater control over the network because more information passes through that node. The IT entity-relations of “mobile” had the highest score at 0.043466. The top pairs were related to depression, mobile health, and text message.ConclusionsE-mental related publications were associated with various research fields, such as nursing, psychology, medical informatics, computer science, telecommunication, and healthcare innovation. We found that trends in e-mental health research are continually rising. These trends were related to the internet of things (IoT) and mobile applications (Apps), which were applied for mental healthcare services. Moreover, producing AI and machine learning for e-mental healthcare were being studied. This work supports the appropriate approaches and methods of e-mental health research that can help the researcher to identify important themes and choose the best fit with their own survey work.

Effects of E-Government Policy on the Management of Healthcare Systems.

E-government began by addressing the challenges of new technologies by delivering e-services to its citizens and has since evolved to include a growing number of areas, such as citizen communication, macroeconomic projections, budget management, and e-healthcare services. E-government is known as the use of information technology to provide administrative services, communication transactions, information exchange, integration of various electronic systems, and autonomous services between the government and citizens, the government and business environment, and the government and government. This paper discusses the role of E-government policy in healthcare crises during COVID 19. Data collected from 435 employees in the tourism industry of Iraq was used to verify the abovementioned relationships via SPSS macro. The results indicate that E-government policy has a significant effect on healthcare crises; job insecurity negatively predicted healthcare crises. The results revealed that social support moderated the relationship between E-government policy and job insecurity. Results of the study contributed to the theory within this study by demonstrating that employees who enjoy a high level of social support show less job insecurity than those with a low level of social support.

Hybrid Whale Optimization Algorithm for Resource Optimization in Cloud E-Healthcare Applications

In the next generation of computing environment e-health care services depend on cloud services. The Cloud computing environment provides a real-time computing environment for e-health care applications. But these services generate a huge number of computational tasks, real-time computing and comes with a deadline, so conventional cloud optimization models cannot fulfil the task in the least time and within the deadline. To overcome this issue many resource optimization meta-heuristic models are been proposed but these models cannot find a global best solution to complete the task in the least time and manage utilization with the least simulation time. In order to overcome existing issues, an artificial neural-inspired whale optimization is proposed to provide a reliable solution for healthcare applications. In this work, two models are proposed one for reliability estimation and the other is based on whale optimization technique and neural network-based binary classifier. The predictive model enhances the quality of service using performance metrics, makespan, least average task completion time, resource usages cost and utilization of the system. From results as compared to existing algorithms the proposed ANN-WHO algorithms prove to improve the average start time by 29.3%, average finish time by 29.5% and utilization by 11%.

An optimal selection of virtual machine for e-healthcare services in cloud data centres

An optimal selection of virtual machine for e-healthcare services in cloud data centres

An optimal selection of virtual machine for e-healthcare services in cloud data centres

An optimal selection of virtual machine for e-healthcare services in cloud data centres

Confidentiality Guaranteed E-Health Treatment for Cloud Cover Enhanced Systems Based on IoT

The advances made with Internet-of- Things (IoTs) on networking technologies and hardware has made for an at the moment more relaxed human life. In addition to the so -called “intelligent” settings, e-healthcare services, as well as real-time diagnoses and diagnostic consulting, have increasingly been integrated into IoT. Cloud cover layers have also been hired, and have demonstrated their utility by offering quick response time and low latency to increase the capability of IoT based health systems. Such a development, however, retains the privacy of users as a serious obstacle, to some degree solving security/privacy problems. Such technology still had less privacy controls when it was at a childhood stage. Therefore, our latest work is on an eHealth System for the security of privacy problems in electronic medical reports (EMR). In addition, we have interacted with and compared work on the proposed work in terms of reaction time and delay. The findings demonstrate the complete work in conjunction with normal network parameters is effective to provide privacy.

Lightweight Multi-party Authentication and Key Agreement Protocol in IoT-based E-Healthcare Service

Internet of Things (IoT) is playing a promising role in e-healthcare applications in the recent decades; nevertheless, security is one of the crucial challenges in the current field of study. Many healthcare devices (for instance, a sensor-augmented insulin pump and heart-rate sensor) collect a user’s real-time data (such as glucose level and heart rate) and send them to the cloud for proper analysis and diagnosis of the user. However, the real-time user’s data are vulnerable to various authentication attacks while sending through an insecure channel. Besides that, the attacks may further open scope for many other subsequent attacks. Existing security mechanisms concentrate on two-party mutual authentication. However, an IoT-enabled healthcare application involves multiple parties such as a patient, e-healthcare test-equipment, doctors, and cloud servers that requires multi-party authentication for secure communication. Moreover, the design and implementation of a lightweight security mechanism that fits into the resource constraint IoT-enabled healthcare devices are challenging. Therefore, this article proposes a lightweight, multi-party authentication and key-establishment protocol in IoT-based e-healthcare service access network to counter the attacks in resource constraint devices. The proposed multi-party protocol has used a lattice-based cryptographic construct such as Identity-Based Encryption (IBE) to acquire security, privacy, and efficiency. The study provided all-round analysis of the scheme, such as security, power consumption, and practical usage, in the following ways. The proposed scheme is tested by a formal security tool, Scyther, to testify the security properties of the protocol. In addition, security analysis for various attacks and comparison with other existing works are provided to show the robust security characteristics. Further, an experimental evaluation of the proposed scheme using IBE cryptographic construct is provided to validate the practical usage. The power consumption of the scheme is also computed and compared with existing works to evaluate its efficiency.

A Novel Cloud-Assisted Secure Deep Feature Classification Framework for Cancer Histopathology Images

The advancements in the Internet of Things (IoT) and cloud services have enabled the availability of smart e-healthcare services in a distant and distributed environment. However, this has also raised major privacy and efficiency concerns that need to be addressed. While sharing clinical data across the cloud that often consists of sensitive patient-related information, privacy is a major challenge. Adequate protection of patients’ privacy helps to increase public trust in medical research. Additionally, DL-based models are complex, and in a cloud-based approach, efficient data processing in such models is complicated. To address these challenges, we propose an efficient and secure cancer diagnostic framework for histopathological image classification by utilizing both differential privacy and secure multi-party computation. For efficient computation, instead of performing the whole operation on the cloud, we decouple the layers into two modules: one for feature extraction using the VGGNet module at the user side and the remaining layers for private prediction over the cloud. The efficacy of the framework is validated on two datasets composed of histopathological images of the canine mammary tumor and human breast cancer. The application of differential privacy preserving to the proposed model makes the model secure and capable of preserving the privacy of sensitive data from any adversary, without significantly compromising the model accuracy. Extensive experiments show that the proposed model efficiently achieves the trade-off between privacy and model performance.

A real-time secure medical device authentication for personal E-Healthcare services on cloud computing

A real-time secure medical device authentication for personal E-Healthcare services on cloud computing

Hybrid image encryption scheme for secure E-health systems

DNA computing is an area of natural computing inspired by molecular biology. It can be used to perform arithmetic and logic operations on information encoded as DNA strands. Due to the rapid development of network technology, E-health care services are helpful for all patients from anywhere at any time. Patients can use these services through a public channel. The security of patients’ privacy is therefore an essential issue in E-health care. In this paper, an encryption scheme is proposed for hiding patient information in a medical image using the Least Significant Bit algorithm, which involves hiding data in the least bit of image pixels. The image is then compressed with a key which is generated from a combination of six stages of chaotic maps and DNA encoding rules that result in encoding data into a DNA format. The proposed security system was applied to six different medical images, including X-ray images, CT images, and MRI images. The results have been evaluated using several evaluation metrics. The proposed scheme appears to be robust.

A robust and lightweight secure access scheme for cloud based E-healthcare services.

Traditional healthcare services have transitioned into modern healthcare services where doctors remotely diagnose the patients. Cloud computing plays a significant role in this change by providing easy access to patients’ medical records to all stakeholders, such as doctors, nurses, patients, life insurance agents, etc. Cloud services are scalable, cost-effective, and offer a broad range of mobile access to patients’ electronic health record (EHR). Despite the cloud’s enormous benefits like real-time data access, patients’ EHR security and privacy are major concerns. Since the information about patients’ health is highly sensitive and crucial, sharing it over the unsecured wireless medium brings many security challenges such as eavesdropping, modifications, etc. Considering the security needs of remote healthcare, this paper proposes a robust and lightweight, secure access scheme for cloud-based E-healthcare services. The proposed scheme addresses the potential threats to E-healthcare by providing a secure interface to stakeholders and prohibiting unauthorized users from accessing information stored in the cloud. The scheme makes use of multiple keys formed through the key derivation function (KDF) to ensure end-to-end ciphering of information for preventing misuse. The rights to access the cloud services are provided based on the identity and the association between stakeholders, thus ensuring privacy. Due to its simplicity and robustness, the proposed scheme is the best fit for protecting data security and privacy in cloud-based E-healthcare services.

Evaluating the total quality and its role in measuring consumer satisfaction with e-healthcare services using the 5Qs model: a structure equation modeling approach

PurposeThis article initially aims to explore the factors of every quality construct of the 5Qs model of service quality and, second, identify the significant factors affecting the total quality of e-healthcare services and its association with consumer satisfaction using a multidimensional hierarchical 5Qs model of e-healthcare service quality.Design/methodology/approachQuestionnaire-oriented research was performed at three public hospitals of Punjab and Chandigarh. In total, 53 variables were covered in all quality constructs for data collection from the designated public hospitals. The respondents who agreed to have knowledge regarding e-Healthcare services and were availing these services were included in the study. The analysis comprised structural equation modeling technique using AMOS 21.FindingsThe outcomes suggest that the 5Qs model is more comprehensive and can be used to evaluate service quality perceptions using e-Healthcare services. The research identified 11 sub-dimensions for the five quality constructs of the 5Qs model, representing total quality, which is primary to consumer satisfaction. “Overall objectivity” and “technical objectivity” defined the quality of object. The quality of process of e-Healthcare services was characterized by “functionality,” “timeliness” and “responsiveness.” Quality of infrastructure was defined by “technical infrastructure,” “physical infrastructure,” “manpower skills” and “organizational infrastructure.” “Manner of interaction” and “timely interaction” defined the quality of interaction. The atmosphere was represented by only one factor. The results also suggest that quality of infrastructure, quality of interaction and quality of atmosphere play the most significant role in total quality leading to consumer satisfaction.Research limitations/implicationsTheoretical implications: The multidimensional hierarchical model will help the researchers study the e-Healthcare service quality in a more organized manner, and the outcomes of this study can be linked with that of future studies for more generalized application in other public hospitals. The sub-dimensions of each quality construct of the 5Qs model can be applied in private hospitals, and the hierarchical model can be tested in different industries to measure service quality perceptions of the consumerPractical implicationsThe outcomes of the study can be applied in various public sector hospitals to redesign the e-Healthcare services based on consumers' perception for better consumer satisfaction and quality services. This paper identifies the role of each quality construct in e-Healthcare services for improvement in the total quality, which in turn will lead to higher satisfaction for the consumers.Originality/valueIn this study, the original 5Qs model has been used for the first time in a new instrument to understand better and design quality e-Healthcare services. The paper explores the sub-factors of each quality construct and its significance in measuring the total quality.

BIoTHR: Electronic Health Record Servicing Scheme in IoT-Blockchain Ecosystem

The pervasiveness of newly introduced Internet-of-Things (IoT) devices has opened up new opportunities in healthcare systems, for example in facilitating remote patient monitoring. There are, however, security and privacy considerations in the transmission of data from these devices to the backend server, and across heterogeneous IoT networks. In this study, we propose a novel privacy-preserving scheme which is based on blockchain and swarm exchange techniques to facilitate seamless and secure transmission of user data (e.g., electronic health record (EHR)-related information) through secured swarm nodes of peer-to-peer communications. BIoTHR refers to the proposed scheme on the private blockchain-assisted EHR management using IoT. Specifically, new blockchain and swarm exchange infrastructures are suggested as a backbone of the proposed scheme to ensure secure and reliable data transmission and timely monitoring of data sent across IoT networks. An autonomous encryption–decryption mechanism is also utilized, along with a dynamic and modular server assistance technology to deploy EHR transmission in a secure manner. Moreover, several swarm-listen, announcement, peer open and peer closing algorithms are incorporated to employ the actual power of pervasive EHR transmission for better e-healthcare service provisioning. The proposed scheme is developed using the open-source tools of GnuPG, IPFS, and Golang. Proposed study simulates a number of heterogeneous IoT-based health sensor nodes, namely, body temperature, pulse rate, and oxygen saturation, i.e., SPO2, galvanic skin response, and blood glucose in blockchain-assisted swarm exchange framework. The results reveal that the proposed scheme, in terms of blockchain-IoT, swarm exchange and EHR transmission, outperforms several peer techniques.

Multiple dimensions of e-healthcare ethics and its relationship to the ethical concerns of the consumer

PurposeThis study aims to explore the different dimensions of e-healthcare ethics and their relationships, influencing the ethical concerns of the consumer in making ethical e-healthcare choices.Design/methodology/approachA study was conducted at two identified major hospitals of Punjab (a private hospital) and Chandigarh (a public hospital), India providing e-healthcare services with the help of a self-administered questionnaire. The respondents were identified from the waiting areas of the selected hospitals, and only those respondents were selected for the study, who agreed to be aware of e-health services and were using them for some time. The statistical analysis was done using the structural equation modeling technique and included both exploratory and confirmatory factor analysis using SPSS 20 and AMOS 21.FindingsExploratory factor analysis extracted five dimensions of ethical concerns of the consumer, which include service promotion, content quality, candor, professionalism and confidentiality. The results signify that content quality plays a significant role in ethics, followed by candor, service promotion and confidentiality. However, the relationship with professionalism did not prove to be significant for the ethical concerns of the e-health consumer.Practical implicationsThis research delivers a practical significance in identifying the critical dimensions of the ethical concerns of the consumer while selecting e-health services. It gives an insight into the various dimensions, which should be considered by the e-health providers while crafting e-health services to make it more ethically acceptable by the consumers.Originality/valueBy using e-health services, consumers play an active role in their health-care decisions. The consumers need to consider ethics while choosing health-care services as an ethical judgment will also be the correct judgment. This study helps in the identification of the significant dimensions for the ethical concerns of the consumers.

Qualitative analysis of digital health literacy among university students in Pakistan

ABSTRACT The digitalization of health information has globally impacted the health literacy of educated youth. In the resource-deprived countries like Pakistan, the promotion of digital health literacy can reduce the risks associated with healthcare utilization by improving the health behavior of individuals. Little is known about the digital health literacy in Pakistan. The present study explores the cognitive, social, and cultural factors of digital health literacy and e-healthcare services utilization among educated youth in Pakistan. We conducted sixteen Focused Group Discussion among male and female students enrolled in different private and public universities located in Lahore. The data were manually analyzed through thematic analysis. We found that the complex presentation of e-health information was linked with a low level of e-health literacy. In addition, inadequate training, poor accessibility to digital resources, and unauthentic websites are the main barricades of digital healthcare services. Concise and simple presentation of online health information, institutional sensitivity about provision of e-healthcare training and easy access to advance digital resources can promote e-health literacy. To cope with the changing global healthcare environment, rigorous efforts and synchronized actions are needed from public and private sector universities and higher education institution to promote digital healthcare services.

Patient's Feedback Platform for Quality of Services via “Free Text Analysis” in Healthcare Industry

Data analysis of social media posting continues to offer a huge variety of information about the health situation faced by an individual. Social networking or social media websites provide us a wealth of information generated by users in a variety of domains, that generated information are unstructured and unlabeled and are not captured in an exceedingly systematic manner, as info generated is not humanly possible to process due to its size. One traditional way of collecting patients experience is by conducting surveys and questionnaires, as these methods ask fixed questions and are expensive to administer. In this paper, a patient feedback platform (PFP) using free text sentiment analysis is developed to computationally identify and categorize the polarity expressed in a piece of text. Six machine learning latest algorithms have been used as key evaluation for evaluating accuracy of the developed (PFP) model. Results achieved have shown 88 % accuracy on the basis of which it is recommended that developed (PFP) patient feedback platform could be used to improve E-health care services indeed.

PIN53 The Usability Testing of the Integrated E-Healthcare Services (IEHS) Web-Based Application in the Therapy Management of HIV and Tuberculosis in Indonesia

PIN53 The Usability Testing of the Integrated E-Healthcare Services (IEHS) Web-Based Application in the Therapy Management of HIV and Tuberculosis in Indonesia

An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare.

The lifetime of a node in wireless sensor networks (WSN) is directly responsible for the longevity of the wireless network. The routing of packets is the most energy-consuming activity for a sensor node. Thus, finding an energy-efficient routing strategy for transmission of packets becomes of utmost importance. The opportunistic routing (OR) protocol is one of the new routing protocol that promises reliability and energy efficiency during transmission of packets in wireless sensor networks (WSN). In this paper, we propose an intelligent opportunistic routing protocol (IOP) using a machine learning technique, to select a relay node from the list of potential forwarder nodes to achieve energy efficiency and reliability in the network. The proposed approach might have applications including e-healthcare services. As the proposed method might achieve reliability in the network because it can connect several healthcare network devices in a better way and good healthcare services might be offered. In addition to this, the proposed method saves energy, therefore, it helps the remote patient to connect with healthcare services for a longer duration with the integration of IoT services.

Effective Reengineering Computing Model For Ethiopian Health Care Center

The ordinary information get to control framework is to keep up the specific sharing composite Personal Health Information Records (PHIRs)in health center, operations from different health centers in cloud major research looks into in the present IT. A PHIR administration license a patient to making, overseeing, and controlling the individual wellbeing information in one spot through the web, which has made the extra room, recovery, and appropriation of the clinical data progressively effective. Uncommonly, every patient is secure the full control of clinical records and can impart the wellbeing information to an enormous scope of clients with social insurance donors and relatives. Because of the significant expense of building and keep up secured and specific server, numerous PHIR administrations are redistributed to make accessible by client from specialist organizations. Decentralized server farms the emission of CO2 is high and nature get spoiled and polluted by making reusable datacenters the data's or information's can shared through the PHIR's. By this we can keep away from the high emission of CO2, the adaptability; accessibility and similarity are increments according to Moore's law. To share the cutting edge data's from other server farm information with reusable asset and e-Health Care Service in Ethiopian health center.