Parallelism in declarative languages

Imperative programming languages were initially built for uniprocessor systems that evolved out of the Von Neumann machine model. This model of storage oriented computation blocks parallelism and increases the cost of parallel program development and porting. Declarative languages based on mathematical models of computation, seem more suitable for the development of parallel programs. In the first part of this thesis we examine different language families under the declarative paradigm: functional, logic, and constraint languages. Functional languages are based on the abstract model of functions and (lamda)-calculus. They were initially developed for symbolic computation, but today they are commonly used in numerical analysis and many other application areas. Pure lisp is a widely known member of this class. Logic languages are based on first order predicate calculus. Although they were initially developed for theorem proving, fifth generation operating systems are written in them. Most logic languages are descendants or distant relatives of Prolog. Constraint languages are related to logic languages. In a constraint language you define a program object by placing constraints on its structure and its behavior. They were initially used in graphics applications, but today researchers work on using them in parallel computation. Here we will compare and contrast the language classes above, locate advantages and deficiencies, and explain different choices made by language implementors. In the second part of thesis we describe a front end for the CONSUL, a prototype constraint language for programming multiprocessors. The most important features of the front end are compact representation of constraints, type definitions, functional use of relations, and the ability to split programs into multiple files

New Scopes for Practice - Interdisciplinary Webinars for Emergency Medicine and Biomedical Informatics - Health Informatics

This paper presents the early outcomes of the educational cooperation between two European academic associations, namely the European Federation of Medical Informatics (EFMI) and European Society of Emergency Medicine (EUSEM). Two webinars were organized in December 2019 and June 2020 to explore areas where mutual education would be beneficial for interdisciplinary cooperation to advance the digitization of emergency departments for the benefit of patients, health professionals and the health system as a whole. Preliminary findings from the analysis of these two webinars are presented and the steps for further cooperation are outlined.published versionpeerReviewe

Interoperability standards enabling cross-border patient summary exchange

Abstract. In an increasingly mobile world, many citizens and professionals are frequent travellers. Access during unplanned care to their patient summary, their most essential health information, in a form physicians in another country can understand can impact not only their safety, but also the quality and effectiveness of healthcare. International health information technology (HIT) standards such as HL7 CDA have been developed to advance interoperability. Implementation guides (IG) and IHE profiles constrain standards and make them fit for the purpose of specific use cases. A joint effort between HL7, IHE, and HealthStory created Consolidated CDA (C-CDA), a set of harmonized CDA IGs for the US that is cited in the Meaning Use II (MU-II) regulation. In the EU, the Patient Summary (PS) Guideline recently adopted, cites the epSOS IG also based on HL7 CDA, to support cross-border care in the EU and inform national eHealth programs. The Trillium Bridge project supports international standards development by extending the EU PS Guideline to meet MU-II C-CDA in the transatlantic exchange of Electronic Health Records (EHRs). This paper presents preliminary findings from comparing patient summaries in the EU and US and reflects on the challenge of implementing interoperable eHealth systems in the cross-border or transatlantic setting

iCARDEA: Practical Data Integration for the Follow-up of Cardiovascular Implantable Electronic Device Patients in Cardiology Departments

Abstrac

From Raw Data to FAIR Data: The FAIRification Workflow for Health Research

BackgroundFAIR (findability, accessibility, interoperability, and reusability) guidingprinciples seek the reuse of data and other digital research input, output, and objects(algorithms, tools, and workflows that led to that data) making themfindable, accessible,interoperable, and reusable. GO FAIR - a bottom-up, stakeholder driven and self-governedinitiative-defined a seven-step FAIRificationprocessfocusingondata,butalsoindicatingtherequired work for metadata. This FAIRification process aims at addressing the translation ofraw datasets into FAIR datasets in a general way, without considering specific requirementsand challenges that may arise when dealing with some particular types of data.This work was performed in the scope of FAIR4Healthproject. FAIR4Health has received funding from the European Union’s Horizon 2020 research and innovationprogramme under grant agreement number 824666

Informed citizen and empowered citizen in health: results from an European survey

Background: The knowledge about the relationship between health-related activities on the Internet (i.e. informed citizens) and individuals? control over their own experiences of health or illness (i.e. empowered citizens) is valuable but scarce. In this paper, we investigate the correlation between four ways of using the Internet for information on health or illness and citizens attitudes and behaviours toward health professionals and health systems and establish the profile of empowered eHealth citizens in Europe. Methods: Data was collected during April and May 2007 (N = 7022), through computer-assisted telephone interviews (CATI). Respondents from Denmark, Germany, Greece, Latvia, Norway, Poland and Portugal participated in the survey. The profiles were generated using logistic regressions and are based on: a) socio-demographic and health information, b) the level of use of health-related online services, c) the level of use of the Internet to get health information to decide whether to consult a health professional, prepare for a medical appointment and assess its outcome, and d) the impact of online health information on citizens? attitudes and behavior towards health professionals and health systems. Results: Citizens using the Internet to decide whether to consult a health professional or to get a second opinion are likely to be frequent visitors of health sites, active participants of online health forums and recurrent buyers of medicines and other health related products online, while only infrequent epatients, visiting doctors they have never met face-to-face. Participation in online health communities seems to be related with more inquisitive and autonomous patients. Conclusions: The profiles of empowered eHealth citizens in Europe are situational and country dependent. The number of Europeans using the Internet to get health information to help them deal with a consultation is raising and having access to online health information seems to be associated with growing number of inquisitive and self-reliant patients. Doctors are increasingly likely to experience consultations with knowledgeable and empowered patients, who will challenge them in various ways

FAIR4Health: Findable, Accessible, Interoperable and Reusable data to foster Health Research

Due to the nature of health data, its sharing and reuse for research are limited by ethical, legal and technical barriers. The FAIR4Health project facilitated and promoted the application of FAIR principles in health research data, derived from the publicly funded health research initiatives to make them Findable, Accessible, Interoperable, and Reusable (FAIR). To confirm the feasibility of the FAIR4Health solution, we performed two pathfinder case studies to carry out federated machine learning algorithms on FAIRified datasets from five health research organizations. The case studies demonstrated the potential impact of the developed FAIR4Health solution on health outcomes and social care research. Finally, we promoted the FAIRified data to share and reuse in the European Union Health Research community, defining an effective EU-wide strategy for the use of FAIR principles in health research and preparing the ground for a roadmap for health research institutions. This scientific report presents a general overview of the FAIR4Health solution: from the FAIRification workflow design to translate raw data/metadata to FAIR data/metadata in the health research domain to the FAIR4Health demonstrators' performance.This research was financially supported by the European Union’s Horizon 2020 research and innovation programme under the grant agreement No 824666 (project FAIR4Health). Also, this research has been co-supported by the Carlos III National Institute of Health, through the IMPaCT Data project (code IMP/00019), and through the Platform for Dynamization and Innovation of the Spanish National Health System industrial capacities and their effective transfer to the productive sector (code PT20/00088), both co-funded by European Regional Development Fund (FEDER) ‘A way of making Europe’.Peer reviewe

A Front End for CONSUL

CONSUL is a prototype constraint language for programming multiprocessors. In this paper we present a front end for CONSUL that makes the language easier to use than it originally was. The most important features of the front end are compact representation of constraints, type definitions, functional use of relations, and the ability to split programs into multiple files