Using conceptual graphs for clinical guidelines representation and knowledge visualization

The intrinsic complexity of the medical domain requires the building of some tools to assist the clinician and improve the patient’s health care. Clinical practice guidelines and protocols (CGPs) are documents with the aim of guiding decisions and criteria in specific areas of healthcare and they have been represented using several languages, but these are difficult to understand without a formal background. This paper uses conceptual graph formalism to represent CGPs. The originality here is the use of a graph-based approach in which reasoning is based on graph-theory operations to support sound logical reasoning in a visual manner. It allows users to have a maximal understanding and control over each step of the knowledge reasoning process in the CGPs exploitation. The application example concentrates on a protocol for the management of adult patients with hyperosmolar hyperglycemic state in the Intensive Care Unit

OWL-based acquisition and editing of computer-interpretable guidelines with the CompGuide editor

Computer-Interpretable Guidelines (CIGs) are the dominant medium for the delivery of clinical decision support, given the evidence-based nature of their source material. Therefore, these machine-readable versions have the ability to improve practitioner performance and conformance to standards, with availability at the point and time of care. The formalisation of Clinical Practice Guideline knowledge in a machine-readable format is a crucial task to make it suitable for the integration in Clinical Decision Support Systems. However, the current tools for this purpose reveal shortcomings with respect to their ease of use and the support offered during CIG acquisition and editing. In this work, we characterise the current landscape of CIG acquisition tools based on the properties of guideline visualisation, organisation, simplicity, automation, manipulation of knowledge elements, and guideline storage and dissemination. Additionally, we describe the CompGuide Editor, a tool for the acquisition of CIGs in the CompGuide model for Clinical Practice Guidelines that also allows the editing of previously encoded guidelines. The Editor guides the users throughout the process of guideline encoding and does not require proficiency in any programming language. The features of the CIG encoding process are revealed through a comparison with already established tools for CIG acquisition.COMPETE, Grant/Award Number: POCI-01-0145-FEDER-007043; FCT - Fundacao para a Ciencia e Tecnologia, Grant/Award Number: UID/CEC/00319/201

Application of a conceptual framework for the modelling and execution of clinical guidelines as networks of concurrent processes

We present a conceptual framework for modelling clinical guidelines as networks of concurrent processes. This enables the guideline to be partitioned and distributed at run-time across a knowledge-based telemedicine system, which is distributed by definition but whose exact physical configuration can only be determined after design-time by considering, amongst other factors, the individual patient's needs. The framework was applied to model a clinical guideline for gestational diabetes mellitus and to derive a prototype that executes the guideline on a smartphone. The framework is shown to support the full development trajectory of a decision support system, including analysis, design and implementation

Conflict resolution in clinical treatments

Dissertação de mestrado integrado em Engenharia InformáticaCurrently, in the health area, there is a need for systems that provide support for the decision of health professionals through specific recommendations for each patient based on Clinical Practice Guidelines (CPGs) for automatic interpretation. CPGs are documents that have enormous importance in the daily life of health professionals, playing a key role in reducing variations in medical practice, improving the quality of health care, and reducing health care costs. These documents reflect knowledge about how best to diagnose and treat diseases in the form of a list of clinical recommendations. However, there may be conflicts and interactions in the application of these clinical recommendations, that which in their maximum exponent may impair the patient’s clinical condition. These conflicts are transported to decision support systems, creating the need to develop computational methods to solve these same conflicts. In the case of multimorbid patients, this resolution of conflicts can be very problematic because these patients suffer from several pathologies at the same time, and that the use of a drug for one particular pathology may have a detrimental effect on the application of another drug in another pathology. Therefore, the objective of this dissertation topic is the determination of conflicts and interactions between drugs and the determination of these same alternatives.Atualmente na área da saúde, existe uma necessidade de existirem sistemas que forneçam apoio à decisão dos profissionais de saúde através de recomendações específicas para cada paciente com base em protocolos clínicos para interpretação automática. Os protocolos clínicos são documentos que têm enorme importância no dia-a-dia dos profissionais de saúde, desempenhando um papel fundamental na redução das variações na prática médica, na melhoria da qualidade dos cuidados de saúde e na redução dos custos de saúde. Estes documentos reflectem o conhecimento sobre a melhor forma de diagnosticar e tratar doenças na forma de uma lista de recomendações clínicas. Contudo, podem existir conflitos e interações na aplicação destas recomendações clínicas, que no seu expoente máximo poderão levar a um agravamento do estado clínico do paciente, nomeadamente no caso da aplicação de diferentes fármacos. Estes conflitos são transportados para os sistemas de apoio à decisão, criando a necessidade de desenvolver métodos computacionais de resolução destes mesmos conflitos. No caso dos pacientes multimórbidos esta resolução de conflitos pode ser bastante problemática devido ao facto destes pacientes sofrerem de várias patologias ao mesmo tempo, e que a utilização de um fármaco para uma determinada patologia possa vir a ter um efeito nocivo na aplicação de outro fármaco noutra patologia. Sendo assim, o objetivo deste tema de dissertação é a determinação dos conflitos e interações entre fármacos e a determinação dessas mesmas alternativas

Personal Knowledge Models with Semantic Technologies

Conceptual Data Structures (CDS) is a unified meta-model for representing knowledge cues in varying degrees of granularity, structuredness, and formality. CDS consists of: (1) A simple, expressive data-model; (2) A relation ontology which unifies the relations found in cognitive models of personal knowledge management tools, e. g., documents, mind-maps, hypertext, or semantic wikis. (3) An interchange format for structured text. Implemented prototypes have been evaluated

A modular, open-source information extraction framework for identifying clinical concepts and processes of care in clinical narratives

In this thesis, a synthesis is presented of the knowledge models required by clinical informa- tion systems that provide decision support for longitudinal processes of care. Qualitative research techniques and thematic analysis are novelly applied to a systematic review of the literature on the challenges in implementing such systems, leading to the development of an original conceptual framework. The thesis demonstrates how these process-oriented systems make use of a knowledge base derived from workflow models and clinical guidelines, and argues that one of the major barriers to implementation is the need to extract explicit and implicit information from diverse resources in order to construct the knowledge base. Moreover, concepts in both the knowledge base and in the electronic health record (EHR) must be mapped to a common ontological model. However, the majority of clinical guideline information remains in text form, and much of the useful clinical information residing in the EHR resides in the free text fields of progress notes and laboratory reports. In this thesis, it is shown how natural language processing and information extraction techniques provide a means to identify and formalise the knowledge components required by the knowledge base. Original contributions are made in the development of lexico-syntactic patterns and the use of external domain knowledge resources to tackle a variety of information extraction tasks in the clinical domain, such as recognition of clinical concepts, events, temporal relations, term disambiguation and abbreviation expansion. Methods are developed for adapting existing tools and resources in the biomedical domain to the processing of clinical texts, and approaches to improving the scalability of these tools are proposed and evalu- ated. These tools and techniques are then combined in the creation of a novel approach to identifying processes of care in the clinical narrative. It is demonstrated that resolution of coreferential and anaphoric relations as narratively and temporally ordered chains provides a means to extract linked narrative events and processes of care from clinical notes. Coreference performance in discharge summaries and progress notes is largely dependent on correct identification of protagonist chains (patient, clinician, family relation), pronominal resolution, and string matching that takes account of experiencer, temporal, spatial, and anatomical context; whereas for laboratory reports additional, external domain knowledge is required. The types of external knowledge and their effects on system performance are identified and evaluated. Results are compared against existing systems for solving these tasks and are found to improve on them, or to approach the performance of recently reported, state-of-the- art systems. Software artefacts developed in this research have been made available as open-source components within the General Architecture for Text Engineering framework

A manufacturing core concepts ontology to support knowledge sharing

Knowledge sharing across domains is key to bringing down the cost of production and the time to market of products. This thesis is directed to improve the knowledge sharing capability of the present systems that use information and communication technologies. Systems for different domains have structures that are made up of concepts and relations with different semantic interpretations. Therefore, knowledge sharing across such domains becomes an issue. Knowledge sharing across multiple domains can be facilitated through a system that can provide a shared understanding across multiple domains. This requires a rigorous common semantic base underlying the domains across which to share knowledge. [Continues.

MuCIGREF: multiple computer-interpretable guideline representation and execution framework for managing multimobidity care

Clinical Practice Guidelines (CPGs) supply evidence-based recommendations to healthcare professionals (HCPs) for the care of patients. Their use in clinical practice has many benefits for patients, HCPs and treating medical centres, such as enhancing the quality of care, and reducing unwanted care variations. However, there are many challenges limiting their implementations. Initially, CPGs predominantly consider a specific disease, and only few of them refer to multimorbidity (i.e. the presence of two or more health conditions in an individual) and they are not able to adapt to dynamic changes in patient health conditions. The manual management of guideline recommendations are also challenging since recommendations may adversely interact with each other due to their competing targets and/or they can be duplicated when multiple of them are concurrently applied to a multimorbid patient. These may result in undesired outcomes such as severe disability, increased hospitalisation costs and many others. Formalisation of CPGs into a Computer Interpretable Guideline (CIG) format, allows the guidelines to be interpreted and processed by computer applications, such as Clinical Decision Support Systems (CDSS). This enables provision of automated support to manage the limitations of guidelines. This thesis introduces a new approach for the problem of combining multiple concurrently implemented CIGs and their interrelations to manage multimorbidity care. MuCIGREF (Multiple Computer-Interpretable Guideline Representation and Execution Framework), is proposed whose specific objectives are to present (1) a novel multiple CIG representation language, MuCRL, where a generic ontology is developed to represent knowledge elements of CPGs and their interrelations, and to create the multimorbidity related associations between them. A systematic literature review is conducted to discover CPG representation requirements and gaps in multimorbidity care management. The ontology is built based on the synthesis of well-known ontology building lifecycle methodologies. Afterwards, the ontology is transformed to a metamodel to support the CIG execution phase; and (2) a novel real-time multiple CIG execution engine, MuCEE, where CIG models are dynamically combined to generate consistent and personalised care plans for multimorbid patients. MuCEE involves three modules as (i) CIG acquisition module, transfers CIGs to the personal care plan based on the patient’s health conditions and to supply CIG version control; (ii) parallel CIG execution module, combines concurrently implemented multiple CIGs by performing concurrency management, time-based synchronisation (e.g., multi-activity merging), modification, and timebased optimisation of clinical activities; and (iii) CIG verification module, checks missing information, and inconsistencies to support CIG execution phases. Rulebased execution algorithms are presented for each module. Afterwards, a set of verification and validation analyses are performed involving real-world multimorbidity cases studies and comparative analyses with existing works. The results show that the proposed framework can combine multiple CIGs and dynamically merge, optimise and modify multiple clinical activities of them involving patient data. This framework can be used to support HCPs in a CDSS setting to generate unified and personalised care recommendations for multimorbid patients while merging multiple guideline actions and eliminating care duplications to maintain their safety and supplying optimised health resource management, which may improve operational and cost efficiency in real world-cases, as well

Spatial Data Harmonisation in Regional Context in Accordance with INSPIRE Implementing Rules

Spatial data seamless exchange and interoperable usage has become a necessity in efficient data management and competitive positioning in the European Union. Conceptual and technical framework for the spatial data and services interoperability is specified within the EU INSPIRE Directive. The Directive provides flexible and modular structure, giving the opportunity for customisation of the data specifications and usage. From the data publisher level to the European spatial data infrastructure, this opened the question of disharmony of the spatial data structure and sharing. Arisen challenges in data harmonisation process are thus subject of interest for different formalisation approaches. This study approaches the spatial data harmonisation process focusing on the area of Western Balkans, the region of Europe with countries that have similar interest for implementation of the INSPIRE Directive. With the main aim to propose the improvement to regional data harmonisation process, the study is focused on geology as the spatial theme. The study (1) analyses the INSPIRE data harmonisation process, (2) assesses critical factors of the process in the region and (3) tests the implementation of the INSPIRE data model harmonised in accordance with user needs. Results of the analysis present the structure and formalisation concepts of the INSPIRE data model, its extensibility, means for securing interoperability and standardised approach in defining data model elements. Critical factors of the harmonisation process are assessed through semi-structured questionnaire answered by competent representatives of the Western Balkans countries. The results show that, on a regional level, spatial data managers have made progress towards compliance and are familiar with the Directive. However, they lack a coordinated approach and implementation guidance. Aside from the low capacities, due to the current state of the data structures, harmonisation is a highly complex process and a goal that is difficult to reach. The outcomes of the INSPIRE defined harmonisation process and user needs are implemented on a practical example, a INSPIRE Theme Geology dataset from a Western Balkans region stakeholder. The user needs and data model structure characteristics of the regional geology dataset were integrated in the formal description of the source and transformed to target INSPIRE data model. The concept required structuring the source model to meet both INSPIRE and local requirements. The study general aim was reached by implementing the INSPIRE data harmonisation with fulfilling the main objectives – creating market-oriented, interoperable and accessible dataset, meeting national legal requirements towards the geological data management and increasing efficiency of data usage. Further application of the developed approach is seen as the implementation methodology for other INSPIRE themes and other geographical regions.Spatial data seamless usage and exchange has become a necessity in management of natural resources, environmental risk assessment, infrastructural planning and various other industrial domains. Framework for spatial data seamless usage is specified within the EU INSPIRE Directive on the continent-wide level. The Directive enables customisation of the data specifications and usage. However, high-level specification raised the issue of disharmony of the spatial data structure and sharing on regional level. Challenges in data harmonisation process therefore became subject of interest for different research approaches. This study approaches the spatial data harmonisation process focusing on the area of Western Balkans, the region of Europe with countries that have similar interest for implementation of the INSPIRE Directive. With the main aim to propose the improvement to regional data harmonisation process, the study is focused on geology as the spatial theme. The study assesses the regional needs and, in that light, develops the example of geological spatial data harmonisation. The needs and the critical factors of the harmonisation process are assessed through a questionnaire answered by competent representatives of the Western Balkans countries. It was found that spatial data managers in the region have made progress towards compliance and are familiar with the Directive. However, they lack a coordinated approach and implementation guidance. Moreover, the current state of the datasets structure makes harmonisation a complex process and a goal that is difficult to reach. Geology dataset from a Western Balkans region stakeholder was used as a practical example for testing the harmonisation process in accordance with user needs and INSPIRE requirements. The result was harmonised INSPIRE conformant spatial dataset, with validated seamless sharing and usage possibilities of the spatial dataset on both local and EU-wide level. The study showed the possibility of applying the INSPIRE data harmonisation, with fulfilling the main objectives of (1) creating market-oriented, interoperable and accessible dataset, (2) meeting national legal requirements towards the geological data management and (3) increasing efficiency of data usage. Further application of the presented approach is seen as the implementation methodology for other spatial themes and different geographical regions

Kognitivna plauzibilnost formalnih modela semantičkih reprezentacija

This work is focused on formal approaches in cognitive semantics, namely, the formalisation of the conceptual level of representations as the intermediate level between the symbolic and the connectivist one. An account of a selection of existing models is given. It is argued that one of the most important shortcomings that keeps the existing models from being truly cognitively plausible is the fact that they do not properly address the correlations between objects’ perceptible features, which are argued to be causally linked to the underlying, essential properties. The argumentation is supported by empirical evidence, implying the existence and importance of the causal effects in categorisation and inductive learning. It is therefore claimed that any cognitively plausible model of semantic representations needs to be able to adequately describe these cognitive phenomena, which has not been achieved so far. The paper qualitatively sketches out a cognitively motivated semantic representation model based on Gärdenfors’ conceptual space theory, endowed with the capability of describing the correlation of surface properties, thus supporting the notion of psychological essentialism.Gärdenforsov model konceptualnih prostora veoma je razrađen semantički model orijentiran opisu strukture koncepata i kvalitativnih domena koje ih sačinjavaju. U ovomu se radu daje pregled tog i izbor drugih sličnih modela konceptualnih prostora te se naglašava nedostatnost njihove kognitivne plauzibilnosti uslijed zanemarivanja ili kognitivno nedosljednoga opisa korelacija svojstava. Postojanje i važnost korelacijskih učinaka u kategorizaciji i induktivnomu učenju potvrđeni su rezultatima mnogobrojnih empirijskih istraživanja temeljenih na kategorizacijskim i generalizacijskim procjenama ispitanika. Dakle, svaki kognitivno vjerodostojan model semantičkih reprezentacija mora uključivati fenomen kognitivnoga sustava koji se odnosi na automatiziranu detekciju strukturiranih korelacija svojstava. Ti se korelacijski učinci opisuju »teorijom teorijā« (engl. theory–theory), koja tvrdi da kognitivni sustav sadrži mikroteorije o konceptima, a te mu mikroteorije omogućavaju sposobnost automatiziranoga induktivnoga učenja kategorizacije prirodnih vrsta (engl. natural kinds) putem uočenih korelacija među njihovim svojstvima. U ovomu se radu tvrdi da su svojstva dobro strukturiranih, koherentnih koncepata uzročno povezana, a ta se povezanost modelira dubinskim, uzročno ishodišnim kvalitativnim dimenzijama. Kao budući rad spominje se istraživanje mogućnosti automatiziranog ili poluautomatiziranog crpljenja parametara predloženoga modela uporabom digitalnih jezičnih resursa kao što su ontologije, Wordnet, liste svojstava koncepata koje su generirali ispitanici temeljem osjetilnih iskustava, odnosno korpusi. Time bi se ostvarilo kombiniranje iskustvenih podataka s podatcima temeljenim na jezičnoj uporabi, što bi tako dobiveni model činilo vrijednim resursom, i za kognitivnu znanost i lingvistiku, kao i za računalnu obradu prirodnoga jezika s naglaskom na semantiku