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The process of maintenance of an underlying semantic model that supports data management and addresses the interoperability challenges in the domain of telemedicine and integrated care is not a trivial task when performed manually. We present a methodology that leverages the provided serializations of the Health Level Seven International (HL7) Fast Health Interoperability Resources (FHIR) specification to generate a fully functional OWL ontology along with the semantic provisions for maintaining functionality upon future changes of the standard. The developed software makes a complete conversion of the HL7 FHIR Resources along with their properties and their semantics and restrictions. It covers all FHIR data types (primitive and complex) along with all defined resource types. It can operate to build an ontology from scratch or to update an existing ontology, providing the semantics that are needed, to preserve information described using previous versions of the standard. All the results based on the latest version of HL7 FHIR as a Web Ontology Language (OWL-DL) ontology are publicly available for reuse and extension. [ABSTRACT FROM AUTHOR]

The global pandemic over the past two years has reset societal agendas by identifying both strengths and weaknesses across all sectors. Focusing in particular on global health delivery, the ability of health care facilities to scale requirements and to meet service demands has detected the need for some national services and organisations to modernise their organisational processes and infrastructures. Core to requirements for modernisation is infrastructure to share information, specifically structural standardised approaches for both operational procedures and terminology services. Problems of data sharing (aka interoperability) is a main obstacle when patients are moving across healthcare facilities or travelling across border countries in cases where emergency treatment is needed. Experts in healthcare service delivery suggest that the best possible way to manage individual care is at home, using remote patient monitoring which ultimately reduces cost burden both for the citizen and service provider. Core to this practice will be advancing digitalisation of health care underpinned with safe integration and access to relevant and timely information. To tackle the data interoperability issue and provide a quality driven continuous flow of information from different health care information systems semantic terminology needs to be provided intact. In this paper we propose and present ContSonto a formal ontology for continuity of care based on ISO 13940:2015 ContSy and W3C Semantic Web Standards Language OWL (Web Ontology Language). ContSonto has several benefits including semantic interoperability, data harmonization and data linking. It can be use as a base model for data integration for different healthcare information models to generate knowledge graph to support shared care and decision making. [ABSTRACT FROM AUTHOR]

This paper focusses on the question of knowledge-based modeling of discharge summaries for semantic requesting in the context of hospital reporting process. An ontology was designed and implemented to capture patient data and required expert knowledge. The modeling process was carried out manually using Protégé after an initial reverse engineering of the official format of discharge summaries. An OWL 2 model was built integrating discharge summaries ontology and ICD 10 hierarchy. The framework is operationalized using the OpenLink Virtuoso database system (RDF store), enabling SPARQL queries and basic reasoning features. The evaluation was performed by implementing a use case based on patient comorbidities. [ABSTRACT FROM AUTHOR]

This paper describes a method by which the Web Ontology Language (OWL) can be used to specify a highly structured health record, following internationally recognised standards such as ISO 13606 and HL7 CDA. The structured record is coded using schemes such as SNOMED, ICD or LOINC, with the coding applied statically, on the basis of the predefined structure, or dynamically, on the basis of data values entered in the health record. The highly structured, coded record can then be linked with external knowledge sources which are themselves coded using the Resource Description Framework. These methods have been used to implement dynamic decision support in the open source cityEHR health records system. The effectiveness of the decision support depends on the scope and quality of the clinical coding and the sophistication of the algorithm used to match the structured record with knowledge sources. [ABSTRACT FROM AUTHOR]

A hot point of phthisiology in Russia during the last decade is the rising morbidity of tuberculosis associated with the drug resistant Micobacteria tuberculosis. The causes of MBT resistance are often related with human factor. Reducing the errors rate in complex Clinical Decision-making in phthisiology requires adequate software support and treatment monitoring. The methodology for structuring of the diagnosis characteristics at the moments of Clinical Decisions in phthisiology is represented. The Quality models and real Clinical Situations have the digital codes. The ontological modeling of the real Clinical Situations is used for analysis, construction the inference rules and improvement of Clinical Decisions and treatment results. [ABSTRACT FROM AUTHOR]

We investigate the application of distributional semantics models for facilitating unsupervised extraction of biomedical terms from unannotated corpora. Term extraction is used as the first step of an ontology learning process that aims to (semi-)automatic annotation of biomedical concepts and relations from more than 300K PubMed titles and abstracts. We experimented with both traditional distributional semantics methods such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) as well as the neural language models CBOW and Skip-gram from Deep Learning. The evaluation conducted concentrates on sepsis, a major life-threatening condition, and shows that Deep Learning models outperform LSA and LDA with much higher precision. [ABSTRACT FROM AUTHOR]

The increasing number of terms used in textbooks for information management (IM) in hospitals makes it difficult for medical informatics students to grasp IM concepts and their interrelations. Formal ontologies which comprehend and represent the essential content of textbooks can facilitate the learning process in IM education. The manual construction of such ontologies is time-consuming and thus very expensive [3]. Moreover, most domain experts lack skills in using a formal language like OWL[2] and usually have no experience with standard editing tools like Protégé 2 [4,5]. This paper presents an ontology modeling approach based on Excel2OWL, a self-developed tool which efficiently supports domain experts in collaboratively constructing ontologies from textbooks. This approach was applied to classic IM textbooks, resulting in an ontology called SNIK. Our method facilitates the collaboration between domain experts and ontologists in the development process. Furthermore, the proposed approach enables ontologists to detect modeling errors and also to evaluate and improve the quality of the resulting ontology rapidly. This approach allows us to visualize the modeled textbooks and to analyze their semantics automatically. Hence, it can be used for e-learning purposes, particularly in the field of IM in hospitals. [ABSTRACT FROM AUTHOR]

ADL is a formal language to express archetypes, independent of standards or domain. However, its specification is not precise enough in relation to the specialization and semantic of archetypes, presenting difficulties in implementation and a few available tools. Archetypes may be implemented using other languages such as XML or OWL, increasing integration with Semantic Web tools. Exchanging and transforming data can be better implemented with semantics oriented models, for example using OWL which is a language to define and instantiate Web ontologies defined by W3C. OWL permits defining significant, detailed, precise and consistent distinctions among classes, properties and relations by the user, ensuring the consistency of knowledge than using ADL techniques. This paper presents a process of an openEHR ADL archetypes representation in OWL ontologies. This process consists of ADL archetypes conversion in OWL ontologies and validation of OWL resultant ontologies using the mutation test. [ABSTRACT FROM AUTHOR]

Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mentalhealth problems. The Galatean Risk and Safety Tool, GRiST, represents mentalhealth expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation. [ABSTRACT FROM AUTHOR]

Standardized terminologies are introduced in healthcare with the intention of improving information quality, which is important for enhancing the quality of healthcare itself. The International Classification for Nursing Practice (ICNP®) is a unified language system that presents an ontology for nursing terminology; it is meant for documentation of nursing diagnoses, nursing interventions and patient outcomes. This paper presents an information model and an application for teaching nursing students how to use ICNP to assist in the planning of nursing care. The model is an integration of ICNP and our catalog ontology, patient journal ontology, and ontology defining task sets. The application for learning nursing terminology offers descriptions of patient situations and then prompts the student to supply nursing statements for diagnoses, goals and interventions. The nursing statements may be selected from catalogues containing premade solutions based on ICNP, or they may be constructed directly by selecting terms from ICNP. [ABSTRACT FROM AUTHOR]

Healthcare information is distributed through multiple heterogeneous and autonomous systems. Access to, and sharing of, distributed information sources are a challenging task. To contribute to meeting this challenge, this paper presents a formal, complete and semi-automatic transformation service from Relational Databases to Web Ontology Language. The proposed service makes use of an algorithm that allows to transform several data models of different domains by deploying mainly inheritance rules. The paper emphasizes the relevance of integrating the proposed approach into an ontology-based interoperability service to achieve semantic interoperability. [ABSTRACT FROM AUTHOR]

Multiple myeloma (MM) is a malignant disorder characterized by the monoclonal proliferation of B cell derived plasma cells in the bone marrow. The diagnosis depends on the identification of abnormal monoclonal marrow plasma cells, monoclonal protein in the serum or urine, evidence of end-organ damage, and a clinical picture consistent with MM. The distinction between MM stages- monoclonal gammopathy of undetermined significance or indolent myeloma-is critical in guiding therapy. This paper describes how to produce ontology-driven semiological rules base (SRB) and a consultation form to aid in the diagnosis of plasma cells diseases. We have extracted the MM sub-ontology from the NCI Thesaurus. Using Protégé 3.4.2 and owl1, criteria in the literature for the diagnosis and staging of MM have been added to the ontology. All quantitative parameters have been transformed to a qualitative format. A formal description of MM variants and stages has been given. The obtained ontology has been checked by a reasoner and instantiated to obtain a SRB. The form created has been tested and evaluated utilizing 63 clinical medical reports. The likelihood for a disease being the correct diagnosis is determined by computing a ratio. The resulting tool is relevant for MM diagnosis and staging. [ABSTRACT FROM AUTHOR]

Expert systems of the 1980s have failed on the difficulties of maintaining large rule bases. The current work proposes a method to achieve and maintain rule bases grounded on ontologies (like NCIT). The process described here for an expert system on plasma cell disorder encompasses extraction of a sub-ontology and automatic and comprehensive generation of production rules. The creation of rules is not based directly on classes, but on individuals (instances). Instances can be considered as prototypes of diseases formally defined by 'destrictions' in the ontology. Thus, it is possible to use this process to make diagnoses of diseases. The perspectives of this work are considered: the process described with an ontology formalized in OWL1 can be extended by using an ontology in OWL2 and allow reasoning about numerical data in addition to symbolic data. [ABSTRACT FROM AUTHOR]

Healthcare data interoperability can only be achieved when the semantics of the content is well defined and consistently implemented across heterogeneous data sources. Achieving these objectives of interoperability requires the collaboration of experts from several domains. This paper describes tooling that integrates Semantic Web technologies with common tools to facilitate cross-domain collaborative development for the purposes of data interoperability. Our approach is divided into stages of data harmonization and representation, model transformation, and instance generation. We applied our approach on Hypergenes, an EU funded project, where we use our method to the Essential Hypertension disease model using a CDA template. Our domain expert partners include clinical providers, clinical domain researchers, healthcare information technology experts, and a variety of clinical data consumers. We show that bringing Semantic Web technologies into the healthcare interoperability toolkit increases opportunities for beneficial collaboration thus improving patient care and clinical research outcomes. [ABSTRACT FROM AUTHOR]

The goal of this work is to build an ontology of Magnetic Resonance Imaging. The MRI domain has been analysed regarding MRI simulators and the DICOM standard. Tow MRI simulators have been analysed: JEMRIS, which is developed in XML and C++, has a hierarchical organisation and SIMRI, which is developed in C, has a good representation of MRI physical processes. To build the ontology we have used Protégé 4, owl2 that allows quantitative representations. The ontology has been validated by a reasoner (Fact++) and by a good representation of DICOM headers and of MRI processes. The MRI ontology would improved MRI simulators and eased semantic interoperability. [ABSTRACT FROM AUTHOR]

A core challenge in biomedical data integration is to enable semantic interoperability between its various stakeholders as well as other interested parties. Promoting the adoption of worldwide accepted information standards along with common controlled terminologies is the right path to achieve this. Our paper describes a solution to this fundamental problem by proposing an approach to semantic data integration based on information models serving as a common language to represent health data coupled with technology that is able to represent the data semantics. We used the HL7 v3 Reference Information Model (RIM) [1] to derive a specific data model for the integrated data, the Web Ontology Language (OWL) [2] to build an ontology that harmonizes the metadata from the disparate data sources, the Unified Modeling Language (UML) [3] to model the data representation, and the Object Constraint Language (OCL) [4] to specify UML model constraints. To illustrate the approach, we use the Essential Hypertension Summary CDA document and related models from Hypergenes, a European Commission funded project [5] exploring the Essential Hypertension disease model. [ABSTRACT FROM AUTHOR]

The amount of biomedical data available in Semantic Web formats has been rapidly growing in recent years. While these formats are machine-friendly, user-friendly web interfaces allowing easy querying of these data are typically lacking. We present “Entrez Neuron”, a pilot neuron-centric interface that allows for keyword-based queries against a coherent repository of OWL ontologies. These ontologies describe neuronal structures, physiology, mathematical models and microscopy images. The returned query results are organized hierarchically according to brain architecture. Where possible, the application makes use of entities from the Open Biomedical Ontologies (OBO) and the ‘HCLS knowledgebase’ developed by the W3C Interest Group for Health Care and Life Science. It makes use of the emerging RDFa standard to embed ontology fragments and semantic annotations within its HTML-based user interface. The application and underlying ontologies demonstrate how Semantic Web technologies can be used for information integration within a curated information repository and between curated information repositories. It also demonstrates how information integration can be accomplished on the client side, through simple copying and pasting of portions of documents that contain RDFa markup. [ABSTRACT FROM AUTHOR]

The harmonization of data protection law in Europe has been theoretically achieved by means of the EU directive on data protection [1]. In practice the harmonization is not absolute and conflicts continue to exist on the ways member states are implementing the directive. The integration of different European medical systems by means of grid technologies will continue to be challenging if technology does not intervene to enhance interoperability between national regulatory frameworks on data protection. In this paper we present an approach to automate privacy requirements for the sharing of patient data across Europe on a healthgrid [2] domain and ensure its enforcement internally and within external domains where the data might travel. This approach is based on the semantic modelling of privacy obligations that are of legal, ethical or cultural nature. These requirements are for the sharing of personal data between different European member states. Our model reflects both similarities and conflicts, if any, between the different member states. This will allow us to reason on the safeguards a data controller should ask from an organization belonging to another member state before disclosing medical data to them. The system will also generate the relevant set of policies to be enforced at the process level of the grid to ensure privacy compliance before allowing access to the data. [ABSTRACT FROM AUTHOR]

Collaborative research can often have demands on finer-grained security that go beyond the authentication-only paradigm as typified by many e-Infrastructure/Grid based solutions. Supporting finer-grained access control is often essential for domains where the specification and subsequent enforcement of authorization policies is needed. The clinical domain is one area in particular where this is so. However it is the case that existing security authorization solutions are fragile, inflexible and difficult to establish and maintain. As a result they often do not meet the needs of real world collaborations where robustness and flexibility of policy specification and enforcement, and ease of maintenance are essential. In this paper we present results of the JISC funded Advanced Grid Authorisation through Semantic Technologies (AGAST) project (www.nesc.ac.uk/hub/projects/agast) and show how semantic-based approaches to security policy specification and enforcement can address many of the limitations with existing security solutions. These are demonstrated into the clinical trials domain through the MRC funded Virtual Organisations for Trials and Epidemiological Studies (VOTES) project (www.nesc.ac.uk/hub/projects/votes) and the epidemiological domain through the JISC funded SeeGEO project (www.nesc.ac.uk/hub/projects/seegeo). [ABSTRACT FROM AUTHOR]

Terminologies are increasingly based on “ontologies” developed in description logics and related languages such as the new Web Ontology Language, OWL. The use of description logic has been expected to reduce ambiguity and make it easier determine logical equivalence, deal with negation, and specify EHRs. However, this promise has not been fully realised: in part because early description logics were relatively inexpressive, in part, because the relation between coding systems, EHRs, and ontologies expressed in description logics has not been fully understood. This paper presents a unifying approach using the expressive formalisms available in the latest version of OWL, OWL 1.1. [ABSTRACT FROM AUTHOR]

Semantic web technologies are used in the construction of a bio-health knowledge base model, which, when coupled with an Electronic Health Record (EHR), is to be used by clinicians. Specifically, this ontology provides the basis for a domain knowledge resource that attempts to bridge biological and clinical information. The prototype is focused on a Cystic Fibrosis exemplar, and the content of the model includes: Cochrane reviews; a time-oriented description; gene therapy; and the most common cystic fibrosis gene mutations. The facts within the model range from nucleo-base mutation and amino acid change to clinical phenotype. The knowledge is represented by layers from the micro level to the macro level. Here, emphasis is placed upon the details between levels (i.e., the vertical axis) and these are made available to bridge the knowledge from different levels. The description of gender, age, mutation and clinical manifestations are clues for matching points within an EHR system. OWL is the ontology representation language used and the output from Protégé-OWL is a XML-based file formatwhich facilitates further application and communication. [ABSTRACT FROM AUTHOR]

How can information technology be used to model and handle clinical knowledge in everyday work so that clinicians can more systematically learn from collected clinical data? Ontology is a crucial element in answering this question. Based on nearly ten years of clinical experience, fundamental requirements of an ontology for oral medicine are presented. The use of the proposed W3C standards RDF and OWL for the design and implementation of an ontology for oral medicine is then described and discussed. The reported work contributes to knowledge representation in oral medicine by presenting the pioneering work towards an ontology for oral medicine using RDF/OWL, thereby testing the latter on a new domain. [ABSTRACT FROM AUTHOR]

The objective of this study is to describe our efforts in a pilot study on modeling diagnostic criteria using a Semantic Webbased approach. We reused the basic framework of the ICD- 11 content model and refined it into an operational model in the Web Ontology Language (OWL). The refinement is based on a bottom-up analysis method, in which we analyzed data elements (including value sets) in a collection (n=20) of randomly selected diagnostic criteria. We also performed a case study to formalize rule logic in the diagnostic criteria of metabolic syndrome using the Semantic Web Rule Language (SWRL). The results demonstrated that it is feasible to use OWL and SWRL to formalize the diagnostic criteria knowledge, and to execute the rules through reasoning. [ABSTRACT FROM AUTHOR]