The openEHR Foundation is an independent, not-for-profit organisation and community, facilitating the creation and sharing of health records by consumers and clinicians via open-source, standards-based implementations. It was formed as a union of ten-year international R&D efforts in specifying the requirements, information models and implementation of comprehensive and ethico-legally sound electronic health record systems. Between 2000 and 2004 it has grown to having an on-line membership of over 300, published a wide range of EHR information viewpoint specifications. Several groups have now begun collaborative software development, within an open source framework. This chapter summarises the formation of openEHR, its research underpinning, practical demonstrators, the principle design concepts, and the roles openEHR members are playing in international standards.

The openEHR Foundation.

Recent technological (e.g., IoT, 5G), and economic (e.g., UN 2030 Sustainable Development Goals) developments have transformed the healthcare sector towards more personalized and IoT-based healthcare services. These services are realized through control and monitoring applications that are typically developed using artificial intelligence (AI)/machine learning (ML) based algorithms, that play a significant role to highlight the efficiency of traditional healthcare systems. Current personalized healthcare services are dedicated in a specific environment to support technological personalization (e.g., personalized gadgets/devices). However, they are unable to consider different inter-related health conditions, leading to inappropriate diagnosis and affect sustainability and the long-term health/life of patients. Towards this problem, the state-of-the-art Healthcare 5.0 technology has evolved that supersede previous healthcare technologies. The goal of healthcare 5.0 is to achieve a fully autonomous healthcare service, that takes into account the interdependent effect of different health conditions of a patient. This paper conducts a comprehensive survey on personalized healthcare services. In particular, we first present an overview of key requirements of comprehensive personalized healthcare services (CPHS) in modern healthcare Internet of Things (HIoT), including the definition of personalization and an example use case scenario as a representative for modern HIoT. Second, we explored a fundamental three-layer architecture for IoT-based healthcare systems using both AI and non-AI-based approaches, considering key requirements for CPHS followed by their strengths and weaknesses in the frame of personalized healthcare services. Third, we highlighted different security threats against each layer of IoT architecture along with the possible AI and non-AI-based solutions. Finally, we propose a methodology to develop reliable, resilient, and personalized healthcare services that address the identified weaknesses of existing approaches. 

/pdf/reliable-and-resilient-ai-and-iot-based-personalised-3v1jfs9j.pdf

Reliable and Resilient AI and IoT-Based Personalised Healthcare Services: A Survey

The rapid development and the expansion of Internet of Things (IoT)-powered technologies have strengthened the way we live and the quality of our lives in many ways by combining Internet and communication technologies through its ubiquitous nature. As a novel technological paradigm, this IoT is being served in many application domains including healthcare, surveillance, manufacturing, industrial automation, smart homes, the military, etc. Medical Internet of Things (MIoT), or the use of IoT in healthcare, is becoming a booming trend towards improving the health and wellbeing of billions of people by offering smooth and seamless medical facilities and by enhancing the services provided by medical practitioners, nurses, pharmaceutical companies, and other related government and non-government organizations. In recent times, this MIoT has gained higher attention for its potential to alleviate the massive burden on global healthcare, which has been caused by the rise of chronic diseases, the aging population, and emergency situations such as the recent COVID-19 global pandemic, where many government and non-government medical resources were challenged, owing to the rising demand for medical resources. It is evident that with this recent growing demand for MIoT, the associated technologies and its interconnected, heterogeneous nature adds new concerns as it becomes accessible to confidential patient data, often without patient or the medical staff consciousness, as the security and privacy of MIoT devices and technologies are often overlooked and undermined by relevant stakeholders. Hence, the growing security breaches that target the MIoT in healthcare are making the security and privacy of Medical IoT a crucial topic that is worth scrutinizing. In this study, we examined the current state of security and privacy of the MIoT, which has become of utmost concern among many security experts and researchers due to its rapid demand in recent times. Nevertheless, pertaining to the current state of security and privacy, we also examine and discuss a number of attack use cases, countermeasures and solutions, recent challenges, and anticipated future directions where further attention is required through this study.

Security and Privacy Issues in Medical Internet of Things: Overview, Countermeasures, Challenges and Future Directions

Bioelectrical impedance analysis and bioelectrical impedance spectroscopy (BIA/BIS) of tissues reveal important information on molecular composition and physical structure that is useful in diagnostics and prognostics. The heterogeneity in structural elements of cells, tissues, organs, and the whole human body, the variability in molecular composition arising from the dynamics of biochemical reactions, and the contributions of inherently electroresponsive components, such as ions, proteins, and polarized membranes, have rendered bioimpedance challenging to interpret but also a powerful evaluation and monitoring technique in biomedicine. BIA/BIS has thus become the basis for a wide range of diagnostic and monitoring systems such as plethysmography and tomography. The use of BIA/BIS arises from (i) being a noninvasive and safe measurement modality, (ii) its ease of miniaturization, and (iii) multiple technological formats for its biomedical implementation. Considering the dependency of the absolute and relative values of impedance on frequency, and the uniqueness of the origins of the α-, β-, δ-, and γ-dispersions, this targeted review discusses biological events and underlying principles that are employed to analyze the impedance data based on the frequency range. The emergence of BIA/BIS in wearable devices and its relevance to the Internet of Medical Things (IoMT) are introduced and discussed.

Bioelectrical Impedance Spectroscopy for Monitoring Mammalian Cells and Tissues under Different Frequency Domains: A Review

The Internet of Things (IoT) is becoming an emerging trend and has significant potential to replace other technologies, where researchers consider it as the future of the internet. It has given tremendous support and become the building blocks in the development of important cyber-physical systems and it is being severed in a variety of application domains, including healthcare. A methodological evolution of the Internet of Things, enabled it to extend to the physical world beyond the electronic world by connecting miscellaneous devices through the internet, thus making everything is connected. In recent years it has gained higher attention for its potential to alleviate the strain on the healthcare sector caused by the rising and aging population along with the increase in chronic diseases and global pandemics. This paper surveys about various usages of IoT healthcare technologies and reviews the state of the art services and applications, recent trends in IoT based healthcare solutions, and various challenges posed including security and privacy issues, which researchers, service providers and end users need to pay higher attention. Further, this paper discusses how innovative IoT enabled technologies like cloud computing, fog computing, blockchain, and big data can be used to leverage modern healthcare facilities and mitigate the burden on healthcare resources.

The Role of the Internet of Things in Health Care: A Systematic and Comprehensive Study

The Medical information is one of the types of information that are characterized by the multiplicity and diversity of its sources. This diversity contributes to the emergence of many problems; of which the most important is the difficulty of communication and interaction between systems. This is what is called the problem of interoperability. In this context, we propose in this paper a new mediator semantic that we call the Medical Project Management System. Based on ontological components and an XML data exchange format, this mediator allows the user to have a unified representation of the information originally distributed on several different and heterogeneous sites and which are related to a specific project. In addition, it helps the user to interact with a large number of medical projects and to research similar projects and comparing them to take advantage of best practices and shared experiences to improve the quality of treatment.

The medical project management (MPM) system

Navigating through the web of uncertain data has become increasingly difficult. Unfortunately, the old techniques used in the classical web can not handle the navigation of uncertain web data or resources. Uncertain data published on the web can be heterogeneous, conflicting, inconsistent or in incompatible formats. This uncertainty is inherently related to many factors such as information extraction and data integration. In order to give the web user the best experience and provide him with the most relevant answer we have to consider the uncertainty of web data and model it. In this paper, we propose a probabilistic approach to model and interpret uncertain web resources. We present operators to compute the uncertainty for the response. Finally, we propose algorithms in order to validate resources and to achieve the uncertain navigation.

A Probabilistic Approach: A Model for the Uncertain Representation and Navigation of Uncertain Web Resources

With the emergence of cloud computing paradigms, secure data outsourcing has become one of the crucial challenges which strongly imposes itself. Data owners place their data among cloud service pro...

https://www.tandfonline.com/doi/pdf/10.1080/24751839.2020.1819633

Secure data outsourcing in presence of the inference problem: issues and directions

Traditional access control models aim to prevent data leakage via direct accesses. A direct access occurs when a requester performs his query directly into the desired object, however these models fail to protect sensitive data from being accessed with inference channels. An inference channel is produced by the combination of a legitimate response which the user receives from the system and metadata. Detecting and removing inference in database systems guarantee a high quality design in terms of data secrecy and privacy. Parting from the fact that data distribution exacerbates inference problem, we give in this paper a survey of the current and emerging research on the inference problem in both centralized and distributed database systems and highlighting research directions in this field.

Inference Control in Distributed Environment: A Comparison Study

Collective intelligence and Knowledge Exploration (CI and KE) have been adopted to solve many problems. They are particularly used by companies as a support for innovation to efficiently obtain usable results. CI is usually defined as a group ability to perform consistently well across a wide variety of tasks, and it has to be combined with KD to ensure processes optimization, efficient management process, participative management, leadership, continuous teamwork, and so on. The importance of innovation grows the same way as the importance of mixing CI and KE, ensuring the successful exploitation of knowledge. Here, we present a quick review of current knowledge-oriented CI developments and applications. It aims at showing some observations about what's currently missing. Our editorial presents some recent interesting studies that we have gathered after a tight selection process. It also concludes by proposing avenue challenges to continue pushing CI and KE research forward, particularly regarding knowledge exploration. 

/pdf/collective-intelligence-and-knowledge-exploration-an-2r27ua43.pdf

Collective intelligence and knowledge exploration: an introduction

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Salma Sassi

Author Tools

Chat about Author