D-WISE: Diabetes Web-Centric Information and Support Environment: Conceptual Specification and Proposed Evaluation

AbstractObjectiveTo develop and evaluate Diabetes Web-Centric Information and Support Environment (D-WISE) that offers 1) a computerized decision-support system to assist physicians to A) use the Canadian Diabetes Association clinical practice guidelines (CDA CPGs) to recommend evidence-informed interventions; B) offer a computerized readiness assessment strategy to help physicians administer behaviour-change strategies to help patients adhere to disease self-management programs; and 2) a patient-specific diabetes self-management application, accessible through smart mobile devices, that offers behaviour-change interventions to engage patients in self-management.MethodsThe above-mentioned objectives were pursued through a knowledge management approach that involved 1) Translation of paper-based CDA CPGs and behaviour-change models as computerized decision-support tools that will assist physicians to offer evidence-informed and personalized diabetes management and behaviour-change strategies; 2) Engagement of patients in their diabetes care by generating a diabetes self-management program that takes into account their preferences, challenges and needs; 3) Empowering patients to self-manage their condition by providing them with personalized educational and motivational messages through a mobile self-management application. The theoretical foundation of our research is grounded in behaviour-change models and healthcare knowledge management.We used 1) knowledge modelling to computerize the paper-based CDA CPGs and behaviour-change models, in particular, the behaviour-change strategy elements of A) readiness-to-change assessments; B) motivation-enhancement interventions categorized along the lines of patients' being ready, ambivalent or not ready; and C) self-efficacy enhancement. The CDA CPGs and the behaviour-change models are modelled and computerized in terms of A) a diabetes management ontology that serves as the knowledge resource for all the services offered by D-WISE; B) decision support services that use logic-based reasoning algorithms to utilize the knowledge encoded within the diabetes management ontology to assist physicians by recommending patient-specific diabetes-management interventions and behaviour-change strategies; C) a mobile diabetes self-management application to engage and educate diabetes patients to self-manage their condition in a home-based setting while working in concert with their family physicians.ResultsWe have been successful in creating and conducting a usability assessment of the physician decision support tool. These results will be published once the patient self- management application has been evaluated.ConclusionsD-WISE will be evaluated through pilot studies measuring 1) the usability of the e-Health interventions; and 2) the impact of the interventions on patients' behaviour changes and diabetes control

Ontological foundations for structural conceptual models

In this thesis, we aim at contributing to the theory of conceptual modeling and ontology representation. Our main objective here is to provide ontological foundations for the most fundamental concepts in conceptual modeling. These foundations comprise a number of ontological theories, which are built on established work on philosophical ontology, cognitive psychology, philosophy of language and linguistics. Together these theories amount to a system of categories and formal relations known as a foundational ontolog

Metarel, an ontology facilitating advanced querying of biomedical knowledge

Knowledge management has become indispensible in the Life Sciences for integrating and querying the enormous amounts of detailed knowledge about genes, organisms, diseases, drugs, cells, etc. Such detailed knowledge is continuously generated in bioinformatics via both hardware (e.g. raw data dumps from micro‐arrays) and software (e.g. computational analysis of data). Well‐known frameworks for managing knowledge are relational databases and spreadsheets. The doctoral dissertation describes knowledge management in two more recently‐investigated frameworks: ontologies and the Semantic Web. Knowledge statements like ‘lions live in Africa’ and ‘genes are located in a cell nucleus’ are managed with the use of URIs, logics and the ontological distinction between instances and classes. Both theory and practice are described. Metarel, the core subject of the dissertation, is an ontology describing relations that can bridge the mismatch between network‐based relations that appeal to internet browsing and logic‐based relations that are formally expressed in Description Logic. Another important subject of the dissertation is BioGateway, which is a knowledge base that has integrated biomedical knowledge in the form of hundreds of millions of network‐based relations in the RDF format. Metarel was used to upgrade the logical meaning of these relations towards Description Logic. This has enabled to build a computer reasoner that could run over the knowledge base and derive new knowledge statements

Ontology based data warehousing for mining of heterogeneous and multidimensional data sources

Heterogeneous and multidimensional big-data sources are virtually prevalent in all business environments. System and data analysts are unable to fast-track and access big-data sources. A robust and versatile data warehousing system is developed, integrating domain ontologies from multidimensional data sources. For example, petroleum digital ecosystems and digital oil field solutions, derived from big-data petroleum (information) systems, are in increasing demand in multibillion dollar resource businesses worldwide. This work is recognized by Industrial Electronic Society of IEEE and appeared in more than 50 international conference proceedings and journals

Multi-Agent Systems

This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019

A framework for analyzing changes in health care lexicons and nomenclatures

Ontologies play a crucial role in current web-based biomedical applications for capturing contextual knowledge in the domain of life sciences. Many of the so-called bio-ontologies and controlled vocabularies are known to be seriously defective from both terminological and ontological perspectives, and do not sufficiently comply with the standards to be considered formai ontologies. Therefore, they are continuously evolving in order to fix the problems and provide valid knowledge. Moreover, many problems in ontology evolution often originate from incomplete knowledge about the given domain. As our knowledge improves, the related definitions in the ontologies will be altered. This problem is inadequately addressed by available tools and algorithms, mostly due to the lack of suitable knowledge representation formalisms to deal with temporal abstract notations, and the overreliance on human factors. Also most of the current approaches have been focused on changes within the internal structure of ontologies, and interactions with other existing ontologies have been widely neglected. In this research, alter revealing and classifying some of the common alterations in a number of popular biomedical ontologies, we present a novel agent-based framework, RLR (Represent, Legitimate, and Reproduce), to semi-automatically manage the evolution of bio-ontologies, with emphasis on the FungalWeb Ontology, with minimal human intervention. RLR assists and guides ontology engineers through the change management process in general, and aids in tracking and representing the changes, particularly through the use of category theory. Category theory has been used as a mathematical vehicle for modeling changes in ontologies and representing agents' interactions, independent of any specific choice of ontology language or particular implementation. We have also employed rule-based hierarchical graph transformation techniques to propose a more specific semantics for analyzing ontological changes and transformations between different versions of an ontology, as well as tracking the effects of a change in different levels of abstractions. Thus, the RLR framework enables one to manage changes in ontologies, not as standalone artifacts in isolation, but in contact with other ontologies in an openly distributed semantic web environment. The emphasis upon the generality and abstractness makes RLR more feasible in the multi-disciplinary domain of biomedical Ontology change management

Towards Cognition-Guided Patient-Specific Numerical Simulation for Cardiac Surgery Assistance

Motivation. Patient-specific, knowledge-based, holistic surgical treatment planning is of utmost importance when dealing with complex surgery. Surgeons need to account for all available medical patient data, keep track of technical developments, and stay on top of current surgical expert knowledge to define a suitable surgical treatment strategy. There is a large potential for computer assistance, also, and in particular, regarding surgery simulation which gives surgeons the opportunity not only to plan but to simulate, too, some steps of an intervention and to forecast relevant surgical situations. Purpose. In this work, we particularly look at mitral valve reconstruction (MVR) surgery, which is to re-establish the functionality of an incompetent mitral valve (MV) through implantation of an artificial ring that reshapes the valvular morphology. We aim at supporting MVR by providing surgeons with biomechanical FEM-based MVR surgery simulations that enable them to assess the simulated behavior of the MV after an MVR. However, according to the above requirements, such surgery simulation is really beneficial to surgeons only if it is patient-specific, surgical expert knowledge-based, comprehensive in terms of the underlying model and the patient’s data, and if its setup and execution is fully automated and integrated into the surgical treatment workflow. Methods. This PhD work conducts research on simulation-enhanced, cognition-guided, patient-specific cardiac surgery assistance. First, we derive a biomechanical MV/MVR model and develop an FEM-based MVR surgery simulation using the FEM software toolkit HiFlow3. Following, we outline the functionality and features of the Medical Simulation Markup Language (MSML) and how it simplifies the biomechanical modeling workflow. It is then detailed, how, by means of the MSML and a set of dedicated MVR simulation reprocessing operators, patient-individual medical data can comprehensively be analyzed and processed in order for the fully automated setup of MVR simulation scenarios. Finally, the presented work is integrated into the cognitive system architecture of the joint research project Cognition-Guided Surgery. We particularly look at its semantic knowledge and data infrastructure as well as at the setup of its cognitive software components, which eventually facilitate cognition-guidance and patient-specifity for the overall simulation-enhanced MVR assistance pipeline. Results and Discussion. We have proposed and implemented, for the first time, a prototypic system for simulation-enhanced, cognition-guided, patient-specific cardiac surgery assistance. The overall system was evaluated in terms of functionality and performance. Through its cognitive, data-driven pipeline setup, medical patient data and surgical information is analyzed and processed comprehensively, efficiently and fully automatically, and the hence set-up simulation scenarios yield reliable, patient-specific MVR surgery simulation results. This indicates the system’s usability and applicability. The proposed work thus presents an important step towards a simulation-enhanced, cognition-guided, patient-specific cardiac surgery assistance, and can – once operative – be expected to significantly enhance MVR surgery. Concluding, we discuss possible further research contents and promising applications to build upon the presented work

Practice-centred e-health system design for cross-boundary clinical decision support

The idea of cross-boundary clinical decision support has the potential to transform the design of future work environments for e-health through a connected healthcare system that allows for harnessing of information and peer opinion across geographical boundaries for better decision-making. The trouble, however, is that the use of healthcare information in decision-making usually occurs within the context of a complex structure of clinical work practices that is often shaped by a wide range of factors, including organisational culture, local work contexts, socially constructed traditions of actions, experiences and patients’ circumstances. They vary across geographical boundaries, and have remained largely unaccounted for in the design of current e-health systems. As a result, achieving the visions of e-health, particularly in relation to cross-boundary clinical decision support, requires a rethinking of key clinical and organisational processes in a manner that accommodates work practice as a fundamental part of how clinicians work and make decisions in the real-world. This thesis investigates the concept of work practice as a design requirement for cross-boundary clinical decision support systems in e-health. It is argued that the task of enabling informed decision support across geographical boundaries in e-health can be enhanced through an understanding, and a formal characterisation, of work practices in various healthcare work contexts, and a specification of how practice can be used, managed and transformed to suit various clinical problem situations and patients’ needs. This research takes a clinical practice-centred approach to inform e-health system design, and draws on the concept of work practice and cultural-historical theory in social science as well as situation awareness in order to describe the local traditions of actions that guide clinicians’ work in the real world. It contributes a coherent conceptual architecture comprising a practice-centred awareness model for cross-boundary awareness, a frame-based technique, named PracticeFrame, for formalising and representing work practice for system design, and ContextMorph, for adaptively transforming a suggestion across work boundaries to suit a user’s local work context and practices. An in-depth user-informed requirements capture was used to gain an understanding of clinical work practices for designing e-health system for cross-boundary decision support. A proof of concept prototype, named CaDHealth, which is based on the Brahms work practice modelling tool and includes a work practice visualisation model, named the practice display, was developed and used to conduct user-based evaluation. The evaluation revealed that incorporating practice-centred awareness enhances usefulness, acceptance and user adoption of e-health systems for cross-boundary clinical decision support