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Cardiovascular diseases (CVDs) aredisorders of the heart and blood vessels and are a major cause of disability and premature death worldwide. Individuals at higher risk of developing CVD must be noticed at an early stage to prevent premature deaths. Advances in the field of computational intelligence, together with the vast amount of data produced daily in clinical settings, have made it possible to create recognition systems capable of identifying hidden patterns and useful information. This paper focuses on the application of Data Mining Techniques (DMTs) to clinical data collected during the medical examination in an attempt to predict whether or not an individual has a CVD. To this end, the CRossIndustry Standard Process for Data Mining (CRISP-DM) methodology was followed, in which five classifiers were applied, namely DT, Optimized DT, RI, RF, and DL. The models were mainly developed using the RapidMiner software with the assist of the WEKA tool and were analyzed based on accuracy, precision, sensitivity, and specificity. The results obtained were considered promising on the basis of the research for effective means of diagnosing CVD, with the best model being Optimized DT, which achieved the highest values for all the evaluation metrics, 73.54%, 75.82%, 68.89%, 78.16% and 0.788 for accuracy, precision, sensitivity, specificity, and AUC, respectively., This work has been supported by FCT - Fundacao para a Ciencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020.

People spend most of their time inside buildings. Therefore, indoor air quality monitoring contributes to improve health and well-being. Several studies focus on the critical impact of particulate matter on residential air quality. In 2016, particulate matter caused 412 thousand premature deaths in 41 European countries. This paper presents the development of an affordable health information system for enhanced living environments. The authors propose a cost-effective, modular, scalable, and easy installation solution for particulate matter monitoring. The system is connected to ThingSpeak. It can be installed in any type of building. It requires only a power source and a Wi-Fi network with internet access. The main contribution of this paper is to present the detailed architecture and testing results. The particulate matter monitoring system was installed for one week in a domestic kitchen with an open fireplace. The results showed impact of the biomass burning on indoor air quality. The mean values per day ranged from: 10.53 to 50.62 μg/m3 for PM1.0, 15.35 to 69.37 μg/m3 for PM2.5, and 20.1 to 90.69 μg/m3 for PM10. The maximum values per hour were registered at 13:00: 72.14 μg/m3 for PM1.0, 99.70 μg/m3 for PM2.5, and 132.13 μg/m3 for PM10. Cost-effective sensors do not have the accuracy level of industrial equipment. Therefore, they should not be used for numerical and in-depth accurate characterization of the environment. Nevertheless, continuous particulate matter monitoring provides consistent data series for analysis of indoor air quality evolution.

Modern network technology yields new interface for telecare medicine information systems in short TMIS used for patient's healthcare. This system is used to provide healthcare services to patients at their home. It can be observed, telecare medicine information systems generally suffer several attacks as information being transmitted over a public network. Therefore, various authentication and key agreement schemes are proposed for TMIS to ensure secure and authorized patients communication over given public network. However, most of the schemes fail to achieve essential attributes discussed in this article. Although the key attributes of security and efficiency should be achieved in a common framework. This paper proposes construction of an RSA based authentication scheme for authorized access to healthcare services and achieves desirable key attributes of authentication protocols. Proof of security against polynomial time adversary is given in the random oracle to justify the security of proposed scheme. Communication analysis and computation analysis of proposed scheme indicates that proposed scheme's performance is comparable and having better security.

The dissemination of electronic medical data among professional personnel has been perceived to be an important breakthrough for the discovery of new technologies and therapies for curing diseases. However, in the current medical data management, it is difficult to share medical data due to the fragmentation of medical data and the lack of effective sharing methods. On the other hand, the security of medical data is difficult to protect because the centralized data storage is vulnerable to attack and tampering. Therefore, we propose a model called Med-PPPHIS, which consists of a permission-less blockchain and a permissioned blockchain, named Med-DLattice, to serve the management of user's personal health information and form a chained protection mechanism for medical data. Med-DLattice features Directed Acyclic Graph (DAG) structure, where each account updates its Account-DAG asynchronously to other unrelated accounts. The Med-DLattice nodes can reach an efficient consensus with proposed DPoS-Quorum algorithm. Based on this model, by converting the medical data into on-chain tokens, a safe and efficient channel for data circulation is established, while the privacy of data is secured. We implement a prototype of Med-PPPHIS and introduce a blockchain-based closed-loop method for chronic disease management, which initially applies the model to national physique monitoring in Anhui Province, China. The performance of the model is evaluated by simulating 500 nodes on 25 AliCloud ECS virtual machines. Experimental result shows that Med-PPPHIS has low latency and high throughput, and the security analysis shows that the model is able to prevent Sybil attacks, DDoS attacks, etc.

Smart Connected Health Systems (SCHSs) belong to health systems that provide services of health care remotely. They provide the doctors with access to electronic medical records with the aid of medical sensors, smart wearable devices and smart medical instruments. Although SCHSs have many applications in the area of health care, securing massive amount of valuable and sensitive data of the patients and preserving the privacy are challenging. User authentication based on public key cryptographic techniques is playing a crucial role in SCHSs for protecting the privacy of patients. However, quantum computers will break such techniques. Rainbow signature is one of the candidates of the next generation of cryptographic algorithms which can resist attacks on quantum computers. However, it is vulnerable to Differential Power Analysis (DPA) attacks, which is based on information gained from the cryptographic implementations. We present techniques to exploit the countermeasures to protect Rainbow against DPA attacks. We propose a variant of Rainbow with resistance to DPA attacks. First, we take a random vector to randomize the power consumption of private keys during computing the first affine transformation; Second, random variables are adopted during computing central map transformation; Third, we take two random vectors during computing the second affine transformation to randomize the power consumption of private keys. We analyze the efficiency and implement the scheme on hardware. Compared with the related implementations, our scheme is efficient and suitable for signature generations on hardware. Besides, we propose a secure authentical scheme based on the implementation for protecting record of patients in SCHSs.

Professor Peter L. Reichertz is one of the most significant pioneers in the field of medical informatics worldwide. In 1969, 50 years ago, he became Professor at the Hannover Medical School. On the occasion of this anniversary an attempt was made to report on the scientific work of Peter Reichertz and to reflect on this work in the light of medical informatics knowledge today. The aim of this study was to search publications listings in the Peter L. Reichertz Archive, in Pubmed/Medline, and in the Web of Science. As well as to analyse contents and communication approaches to help in classifying Peter Reichertz’s scientific publications. Three comprehensive publication lists were identified: the Print Bibliography (384 publications), the Disc Bibliography (285 publications) and the Selected Publications Bibliography (111 publications). Based on the last bibliography, a classification was built along the semantic dimensions of (1) major topics, (2) fields of publication, and (3) publication languages. Major contents of Peter Reichertz’s research in informatics were medical informatics as a field (including education), informatics applications in medicine and health care, and health information systems. Clear shifts over time were observed. To his research on informatics applications, in the 1970s health information systems was added as topic, which then became a major part of his research. While in the 1960s and earlier German was a major publication language, from the 1970s onwards this shifted to English as the major language. Peter Reichertz very early identified the potential of computers in medicine and health care. He did not just use information and communication technology and information processing methodology as if they were other technology, such as microscopes or ultrasonic devices, for improving diagnosis and therapy. He was visionary enough to very early see the revolutionary potential of informatics for biomedicine and health care, with consequential impact on research and education.

Approximately 23% of patients discharged from primary healthcare facilities are readmitted within 30 days at an annual cost of roughly $42 billion. To remedy this problem, healthcare providers are attempting to deploy readmission risk estimation tools, but how they might be used in the traditional, human-expert-centered decision process is not well understood. One such tool estimates readmission risk based on 50 patient-specific factors. This paper reports on a study performed in collaboration with Order of St. Francis Healthcare to determine how healthcare workers’ own risk estimates are influenced by the tool, specifically testing the hypothesis that they will first anchor towards tool results while making adjustments based on their expertise, and then make further adjustments when additional human expert opinions are presented. Task analysis was performed, fictional patient scenarios were developed, and a survey of 56 subjects in two stratified groups of case managers was conducted. Data from the control and experiment groups were analyzed using ANOVA/GLM and t-tests. Results indicate that the healthcare workers’ risk estimates were influenced by the anchor provided by the tool, then adjusted based on their expertise. The workers further adjusted their estimates in response to new expert human inputs. Thus, a reliance on both the predictive model and human expertise was observed.

In real-time medical systems, the role of biometric technology is significant in authentication systems because it is used in verifying the identity of people through their biometric features. The biometric technology provides crucial properties for biometric features that can support the process of personal identification. The storage of biometric template within a central database makes it vulnerable to attack which can also occur during data transmission. Therefore, an alternative mechanism of protection becomes important to develop. On this basis, this study focuses on providing a detailed analysis of the extant literature (2013-2018) to identify the taxonomy and research distribution. Furthermore, this study also seeks to ascertain the challenges and motivations associated with biometric steganography in real-time medical systems to provide recommendations that can enhance the efficient use of real-time medical systems in biometric steganography and its applications. A review of articles on human biometric steganography in real-time medical systems obtained from three main databases (IEEE Xplore, ScienceDirect and Web of Science) is conducted according to an appropriate review protocol. Then, 41 related articles are selected by using exclusion and inclusion criteria. Majority of the studies reviewed had been conducted in the field of data-hiding (particularly steganography) technologies. In this review, various steganographic methods that have been applied in different human biometrics are investigated. Thereafter, these methods are categorised according to taxonomy, and the results are presented on the basis of human steganography biometric real-time medical systems, testing and evaluation methods, significance of use and applications and techniques. Finally, recommendations on how the challenges associated with data hiding can be addressed are provided to enhance the efficiency of using biometric information processed in any authentication real-time medical system. These recommendations are expected to be immensely helpful to developers, company users and researchers.

The increasing demand for Android mobile devices and blockchain has motivated malware creators to develop mobile malware to compromise the blockchain. Although the blockchain is secure, attackers have managed to gain access into the blockchain as legal users, thereby comprising important and crucial information. Examples of mobile malware include root exploit, botnets, and Trojans and root exploit is one of the most dangerous malware. It compromises the operating system kernel in order to gain root privileges which are then used by attackers to bypass the security mechanisms, to gain complete control of the operating system, to install other possible types of malware to the devices, and finally, to steal victims' private keys linked to the blockchain. For the purpose of maximizing the security of the blockchain-based medical data management (BMDM), it is crucial to investigate the novel features and approaches contained in root exploit malware. This study proposes to use the bio-inspired method of practical swarm optimization (PSO) which automatically select the exclusive features that contain the novel android debug bridge (ADB). This study also adopts boosting (adaboost, realadaboost, logitboost, and multiboost) to enhance the machine learning prediction that detects unknown root exploit, and scrutinized three categories of features including (1) system command, (2) directory path and (3) code-based. The evaluation gathered from this study suggests a marked accuracy value of 93% with Logitboost in the simulation. Logitboost also helped to predicted all the root exploit samples in our developed system, the root exploit detection system (RODS).

The widespread deployment and utility of Wireless Body Area Networks (WBAN's) in healthcare systems required new technologies like Internet of Things (IoT) and cloud computing, that are able to deal with the storage and processing limitations of WBAN's. This amalgamation of WBAN-based healthcare systems to cloud-based healthcare systems gave rise to serious privacy concerns to the sensitive healthcare data. Hence, there is a need for the proactive identification and effective mitigation mechanisms for these patient's data privacy concerns that pose continuous threats to the integrity and stability of the healthcare environment. For this purpose, a systematic literature review has been conducted that presents a clear picture of the privacy concerns of patient's data in cloud-assisted healthcare systems and analyzed the mechanisms that are recently proposed by the research community. The methodology used for conducting the review was based on Kitchenham guidelines. Results from the review show that most of the patient's data privacy techniques do not fully address the privacy concerns and therefore require more efforts. The summary presented in this paper would help in setting research directions for the techniques and mechanisms that are needed to address the patient's data privacy concerns in a balanced and light-weight manner by considering all the aspects and limitations of the cloud-assisted healthcare systems.

The security effectiveness based on users' behaviors is becoming a top priority of Health Information System (HIS). In the first step of this study, through the review of previous studies `Self-efficacy in Information Security' (SEIS) and `Security Competency' (SCMP) were identified as the important factors to transforming HIS users to the first line of defense in the security. Subsequently, a conceptual model was proposed taking into mentioned factors for HIS security effectiveness. Then, this quantitative study used the structural equation modeling to examine the proposed model based on survey data collected from a sample of 263 HIS users from eight hospitals in Iran. The result shows that SEIS is one of the important factors to cultivate of good end users' behaviors toward HIS security effectiveness. However SCMP appears a feasible alternative to providing SEIS. This study also confirms the mediation effects of SEIS on the relationship between SCMP and HIS security effectiveness. The results of this research paper can be used by HIS and IT managers to implement their information security process more effectively.

To introduce smart health in Wuhan, and provide some references for other cities. As the largest mega-city in central China, Wuhan is investing large amounts of resources to push forward the development of Smart Wuhan and Health Wuhan, and it has unique features. It is one of the centerpieces of China's New Healthcare Reform, and great hope is put on it to help solve the conflict between limited healthcare resources and the large population of patients. How to plan and design smart health is important. The construction of Wuhan Smart Health includes some aspects as follows, like requirement analysis, the establishment of objectives and blueprint, the architecture design of regional health information platform, evaluation and implementation, problems and solutions, and so on. Wuhan Smart Health has obtained some achievements in health network, information systems, resident's health records, information standard, and the first phase of municipal health information platform. The focus of this article is the whole construction process of smart health in Wuhan. Although there are some difficulties during this period, some smart health services and management have been reflected. Compared with other cities or countries, Wuhan Smart Health has its own advantages and disadvantages. This study aims to provide a reference for other cities. Because smart health of Wuhan is characteristic in construction mode. Though still in the initial stage, it has great potentials in the future.

The Telecare Medicine Information Systems (TMISs) provide an efficient communicating platform supporting the patients access health-care delivery services via internet or mobile networks. Authentication becomes an essential need when a remote patient logins into the telecare server. Recently, many extended chaotic maps based authentication schemes using smart cards for TMISs have been proposed. Li et al. proposed a secure smart cards based authentication scheme for TMISs using extended chaotic maps based on Lee's and Jiang et al.'s scheme. In this study, we show that Li et al.'s scheme has still some weaknesses such as violation the session key security, vulnerability to user impersonation attack and lack of local verification. To conquer these flaws, we propose a chaotic maps and smart cards based password authentication scheme by applying biometrics technique and hash function operations. Through the informal and formal security analyses, we demonstrate that our scheme is resilient possible known attacks including the attacks found in Li et al.'s scheme. As compared with the previous authentication schemes, the proposed scheme is more secure and efficient and hence more practical for telemedical environments.

Filiació URV: SIInclós a la Memòria: Sí Intelligent agents and healthcare have been intimately linked in the last years. The intrinsic complexity and diversity of care can be tackled with the flexibility, dynamics and reliability of multi-agent systems. The purpose of this review is to show the feasibility of applying intelligent agents in the healthcare domain and use the findings to provide a discussion of current trends and devise future research directions. A review of the most recent literature (2009-2014) of applications of agents in healthcare is discussed, and two classifications considering the main goal of the health systems as well as the main actors involved have been investigated. This review shows that the number of published works exhibits a growing interest of researchers in this field in a wide range of applications.

Worldwide populations are aging and countries have to prepare for the effects of demographic change in health care. Health information exchange (HIE), which is the process of moving patient information across health care providers electronically, can help overcome health data fragmentation and open opportunities to improve patient care in terms of quality, economy and efficiency. Since Japan and Germany are among the first countries strongly impacted by demographic changes of aging populations, we report on current developments about health information systems carrying out HIE based on case studies in both countries. Four projects that address the improvement of HIE within a defined region have been selected and investigated: the German project of the Lower Saxony Bank of Health and the Japanese projects Chiba ITnet, Nagasaki AjisaiNet and the National Disaster and Backup System of Japan. The project descriptions are based on relevant English publications, on-site visits and interviews with developers and users. The projects are introduced in terms of their basic architecture and implementation, their present status and future objectives. The projects' developments are still in progress and all have to cope with significant challenges before they will be able to provide a fully working trans-institutional health network solution.

Telecare medical information systems (TMIS), with the explosive growth of communication technology and physiological monitoring devices, are applied increasingly to enable and support healthcare delivery services. In order to safeguard patients' privacy and tackle the illegal access, authentication schemes for TMIS have been investigated and designed by many researchers. Many of them are promising for adoption in practice, nevertheless, they still have security flaws. In this paper, we propose a novel remote authentication scheme for TMIS using self-certified public keys, which is formally secure in the ID-mBJM model. Besides, the proposed scheme has better computational efficiency. Compared to the related schemes, our protocol is more practical for telemedicine system.

Telecare medical information systems (TMIS) provides rapid and convenient health care services remotely. Efficient authentication is a prerequisite to guarantee the security and privacy of patients in TMIS. Authentication is used to verify the legality of the patients and TMIS server during remote access. Very recently Islam et al. (J. Med. Syst. 38(10):135, 2014) proposed a two factor authentication protocol for TMIS using elliptic curve cryptography (ECC) to improve Xu et al.'s (J. Med. Syst. 38(1):9994, 2014) protocol. They claimed their improved protocol to be efficient and provides all security requirements. However our analysis reveals that Islam et al.'s protocol suffers from user impersonation and server impersonation attacks. Furthermore we proposed an enhanced protocol. The proposed protocol while delivering all the virtues of Islam et al.'s protocol resists all known attacks.

The medical organizations have introduced Telecare Medical Information System (TMIS) to provide a reliable facility by which a patient who is unable to go to a doctor in critical or urgent period, can communicate to a doctor through a medical server via internet from home. An authentication mechanism is needed in TMIS to hide the secret information of both parties, namely a server and a patient. Recent research includes patient's biometric information as well as password to design a remote user authentication scheme that enhances the security level. In a single server environment, one server is responsible for providing services to all the authorized remote patients. However, the problem arises if a patient wishes to access several branch servers, he/she needs to register to the branch servers individually. In 2014, Chuang and Chen proposed an remote user authentication scheme for multi-server environment. In this paper, we have shown that in their scheme, an non-register adversary can successfully logged-in into the system as a valid patient. To resist the weaknesses, we have proposed an authentication scheme for TMIS in multi-server environment where the patients can register to a root telecare server called registration center (RC) in one time to get services from all the telecare branch servers through their registered smart card. Security analysis and comparison shows that our proposed scheme provides better security with low computational and communication cost.

Nowadays, with comprehensive employment of the internet, healthcare delivery services is provided remotely by telecare medicine information systems (TMISs). A secure mechanism for authentication and key agreement is one of the most important security requirements for TMISs. Recently, Tan proposed a user anonymity preserving three-factor authentication scheme for TMIS. The present paper shows that Tan's scheme is vulnerable to replay attacks and Denial-of-Service attacks. In order to overcome these security flaws, a new and efficient three-factor anonymous authentication and key agreement scheme for TMIS is proposed. Security and performance analysis shows superiority of the proposed scheme in comparison with previously proposed schemes that are related to security of TMISs.

Heterogeneity in the management of the complex medical data, obstructs the attainment of data level interoperability among Health Information Systems (HIS). This diversity is dependent on the compliance of HISs with different healthcare standards. Its solution demands a mediation system for the accurate interpretation of data in different heterogeneous formats for achieving data interoperability. We propose an adaptive AdapteR Interoperability ENgine mediation system called ARIEN, that arbitrates between HISs compliant to different healthcare standards for accurate and seamless information exchange to achieve data interoperability. ARIEN stores the semantic mapping information between different standards in the Mediation Bridge Ontology (MBO) using ontology matching techniques. These mappings are provided by our System for Parallel Heterogeneity (SPHeRe) matching system and Personalized-Detailed Clinical Model (P-DCM) approach to guarantee accuracy of mappings. The realization of the effectiveness of the mappings stored in the MBO is evaluation of the accuracy in transformation process among different standard formats. We evaluated our proposed system with the transformation process of medical records between Clinical Document Architecture (CDA) and Virtual Medical Record (vMR) standards. The transformation process achieved over 90 % of accuracy level in conversion process between CDA and vMR standards using pattern oriented approach from the MBO. The proposed mediation system improves the overall communication process between HISs. It provides an accurate and seamless medical information exchange to ensure data interoperability and timely healthcare services to patients.

Health information systems (HIS) are a specific area of information systems (IS), where critical patient data is stored and quality health service is only realized with the correct use and efficient dissemination of this data to health workers. Therefore, a balance needs to be established between the levels of security and flow of information on HIS. Instead of implementing higher levels and further mechanisms of control to increase the security of HIS, it is preferable to deal with the arguably weakest link on HIS chain with respect to security: HIS users. In order to provide solutions and approaches for transforming users to the first line of defense in HIS but also to employ capable and appropriate candidates from the pool of newly graduated students, it is important to assess and evaluate the security awareness levels and characteristics of these existing and future users. This study aims to provide a new perspective to understand the phenomenon of security awareness of HIS users with the use of fuzzy analysis, and to assess the present situation of current and future HIS users of a leading medical and educational institution of Turkey, with respect to their security characteristics based on four different security scales. The results of the fuzzy analysis, the guide on how to implement this fuzzy analysis to any health institution and how to read and interpret these results, together with the possible implications of these results to the organization are provided.

In this paper we describe the development of a Personal Health Information System using a knowledge base developed using concept maps. Here we describe a solution for providing the critical need to develop an information capturing system that helps domain experts in developing a graphical representation of the aforementioned knowledge base which can then be converted to a machine--actable form of information. A prototype application has been developed using this information capturing system that clearly demonstrates the use of the knowledge base framework using concept maps to develop Personal Health Information System for lung cancer patients.

The integration of applications is always the most important issue for a development team especially in the healthcare industry. In this paper, a Health Level 7 (HL7) engine system is proposed to solve HL7 challenges, which are associated with applying HL7 in healthcare organizations. This new HL7 engine has been implemented in a hospital as a solution for challenges we have faced. The engine shows great success overcoming known HL7 limitations.

Connected health care provides new opportunities for improving financial and clinical performance. Many connected health care applications such as telecare medicine information system, personally controlled health records system, and patient monitoring have been proposed. Correct and quality care is the goal of connected heath care, and user authentication can ensure the legality of patients. After reviewing authentication schemes for connected health care applications, we find that many of them cannot protect patient privacy such that others can trace users/patients by the transmitted data. And the verification tokens used by these authentication schemes to authenticate users or servers are only password, smart card and RFID tag. Actually, these verification tokens are not unique and easy to copy. On the other hand, biometric characteristics, such as iris, face, voiceprint, fingerprint and so on, are unique, easy to be verified, and hard to be copied. In this paper, a biometrics-based user authentication scheme will be proposed to ensure uniqueness and anonymity at the same time. With the proposed scheme, only the legal user/patient himself/herself can access the remote server, and no one can trace him/her according to transmitted data.

In this paper we present the development of a Personal Health Information System (PHIS) by capturing the domain knowledge in the form of concept maps. The software architecture based on capturing the conceptual domain knowledge is demonstrated using a working prototype for patients suffering from diabetes mellitus. Cited current literature predicts that this user based information system has the potential to improve patient care, reduce medical errors, and lower health care costs.