Binding SNOMED-CT Terms to Archetype Elements: Establishing a Baseline of Results

Introduction: This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". Background: The proliferation of archetypes as a means to represent information of Electronic Health Records has raised the need of binding terminological codes - such as SNOMED CT codes - to their elements, in order to identify them univocally. However, the large size of the terminologies makes it difficult to perform this task manually. Objectives: To establish a baseline of results for the aforementioned problem by using off-the-shelf string comparison-based techniques against which results from more complex techniques could be evaluated. Methods: Nine Typed Comparison METHODS were evaluated for binding using a set of 487 archetype elements. Their recall was calculated and Friedman and Nemenyi tests were applied in order to assess whether any of the methods outperformed the others. Results: Using the qGrams method along with the 'Text' information piece of archetype elements outperforms the other methods if a level of confidence of 90% is considered. A recall of 25.26% is obtained if just one SNOMED CT term is retrieved for each archetype element. This recall rises to 50.51% and 75.56% if 10 and 100 elements are retrieved respectively, that being a reduction of more than 99.99% on the SNOMED CT code set. Conclusions: The baseline has been established following the above-mentioned results. Moreover, it has been observed that although string comparison-based methods do not outperform more sophisticated techniques, they still can be an alternative for providing a reduced set of candidate terms for each archetype element from which the ultimate term can be chosen later in the more-than-likely manual supervision task.Comment: This document is the Accepted Manuscript version of a Published Work that appeared in final form in Methods of Information in Medicine 54(1) : 45-49 (2015), copyright 2015 Schattauer. To access the final edited and published work see https://doi.org/10.3414/me13-02-002

SSDOnt: an Ontology for representing Single-Subject Design Studies

Background: Single-Subject Design is used in several areas such as education and biomedicine. However, no suited formal vocabulary exists for annotating the detailed configuration and the results of this type of research studies with the appropriate granularity for looking for information about them. Therefore, the search for those study designs relies heavily on a syntactical search on the abstract, keywords or full text of the publications about the study, which entails some limitations. Objective: To present SSDOnt, a specific purpose ontology for describing and annotating single-subject design studies, so that complex questions can be asked about them afterwards. Methods: The ontology was developed following the NeOn methodology. Once the requirements of the ontology were defined, a formal model was described in a Description Logic and later implemented in the ontology language OWL 2 DL. Results: We show how the ontology provides a reference model with a suitable terminology for the annotation and searching of single-subject design studies and their main components, such as the phases, the intervention types, the outcomes and the results. Some mappings with terms of related ontologies have been established. We show as proof-of-concept that classes in the ontology can be easily extended to annotate more precise information about specific interventions and outcomes such as those related to autism. Moreover, we provide examples of some types of queries that can be posed to the ontology. Conclusions: SSDOnt has achieved the purpose of covering the descriptions of the domain of single-subject research studies.Comment: This document is the Accepted Manuscript version of a Published Work that appeared in final form in Methods of Information in Medicine 57(01/02) : 55-61 (2018), copyright 2018 Schattauer. To access the final edited and published work see https://doi.org/10.3414/ME17-01-010

Towards the implementation of Industry 4.0: A methodology-based approach oriented to the customer life cycle

Many different worldwide initiatives are promoting the transformation from machine dominant manufacturing to digital manufacturing. Thus, to achieve a successful transformation to Industry 4.0 standard, manufacturing enterprises are required to implement a clear roadmap. However, Small and Medium Manufacturing Enterprises (SMEs) encounter many barriers and difficulties (economical, technical, cultural, etc.) in the implementation of Industry 4.0. Although several works deal with the incorporation of Industry 4.0 technologies in the area of the product and supply chain life cycles, which SMEs could use as reference, this is not the case for the customer life cycle. Thus, we present two contributions that can help the software engineers of those SMEs to incorporate Industry 4.0 technologies in the context of the customer life cycle. The first contribution is a methodology that can help those software engineers in the task of creating new software services, aligned with Industry 4.0, that allow to change how customers interact with enterprises and the experiences they have while interacting with them. The methodology details a set of stages that are divided into phases which in turn are made up of activities. It places special emphasis on the incorporation of semantics descriptions and 3D visualization in the implementation of those new services. The second contribution is a system developed for a real manufacturing scenario, using the proposed methodology, which allows to observe the possibilities that this kind of systems can offer to SMEs in two phases of the customer life cycle: Discover & Shop, and Use & Service.Comment: Accepted version of paper: V\'ictor Julio Ram\'irez-Dur\'an, Idoia Berges, Arantza Illarramendi: Towards the implementation of Industry 4.0: A methodology-based approach oriented to the customer life cycle. Comput. Ind. 126: 103403 (2021). DOI: 10.1016/j.compind.2021.10340

A Semantic Approach for Big Data Exploration in Industry 4.0

The growing trends in automation, Internet of Things, big data and cloud computing technologies have led to the fourth industrial revolution (Industry 4.0), where it is possible to visualize and identify patterns and insights, which results in a better understanding of the data and can improve the manufacturing process. However, many times, the task of data exploration results difficult for manufacturing experts because they might be interested in analyzing also data that does not appear in pre-designed visualizations and therefore they must be assisted by Information Technology experts. In this paper, we present a proposal materialized in a semantic-based visual query system developed for a real Industry 4.0 scenario that allows domain experts to explore and visualize data in a friendly way. The main novelty of the system is the combined use that it makes of captured data that are semantically annotated first, and a 2D customized digital representation of a machine that is also linked with semantic descriptions. Those descriptions are expressed using terms of an ontology, where, among others, the sensors that are used to capture indicators about the performance of a machine that belongs to a Industry 4.0 scenario have been modeled. Moreover, this semantic description allows to: formulate queries at a higher level of abstraction, provide customized graphical visualizations of the results based on the format and nature of the data, and download enriched data enabling further types of analysis.Comment: Published version of paper: Idoia Berges, V\'ictor Julio Ram\'irez-Dur\'an, Arantza Illarramendi: A Semantic Approach for Big Data Exploration in Industry 4.0. Big Data Res. 25: 100222 (2021). DOI: 10.1016/j.bdr.2021.10022

Flexible Access to Services in Smart Cities: Let SHERLOCK Advise Modern Citizens

Citizens can access a variety of computing services to get information, but it is often difficult to know which service will offer the best information. Researchers in the SHERLOCK (System for Heterogeneous mobilE Requests by Leveraging Ontological and Contextual Knowledge) project, from the University of Zaragoza and the Basque Country University, address this by providing mobile users with interesting Location-Based Services (LBSs)

An Ontology Connected to Several Data Repositories: Query Processing Steps

The great expansion of communication networks has made avail- able to users a huge number of heterogeneous and autonomous data repositories that present different structures/organizations, query languages and data semantics. In that context it is clear that new information retrieval techniques with a strategy that focuses on in- formation content and semantics are needed. We propose to use domain specific Ontologies to capture the information content of such repositories whenever available. We describe such Ontolo- gies using a system based on Description Logics. In this paper we present all the stages of the processing of a query formulated over an Ontology when the answer must be found in the underly- ing data repositories. Those stages make up a subpart of the global query processing strategy defined for a set of loosely-coupled On- tologies. We show first how the query is transformed into a seman- tically equivalent one and how inconsistent queries are detected. Then, we explain the test to verify if the query can be answered from the cache memory. Next, we present a set of heuristics used during the query decomposition process. Later on, we show how to optimize plans associated to subqueries that access the underlying data repositories and finally we illustrate how the answers retrieved from the repositories are correlated in order to generate the query answer

Lossless Compression of Industrial Time Series With Direct Access

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] The new opportunities generated by the data-driven economy in the manufacturing industry have causedmany companies opt for it. However, the size of time series data that need to be captured creates theproblem of having to assume high storage costs. Moreover, these costs, which are constantly growing,begin to have an impact on the profitability of companies. Thus, in this scenario, the need arises to developtechniques that allow obtaining reduced representations of the time series. In this paper, we present alossless compression method for industrial time series that allows an efficient access. That is, our aim goesbeyond pure compression, where the usual way to access the data requires a complete decompressionof the dataset before processing it. Instead, our method allows decompressing portions of the dataset,and moreover, it allows direct querying the compressed data. Thus, the proposed method combines theefficient access, typical of lossy methods, with the lossless compression.Xunta de Galicia; ED431G 2019/01Xunta de Galicia; IG240. 2020.1.185Xunta de Galicia; IN852A 2018/14Gobierno Vasco; IT1330-19For the A Coruña team: This work was supported by CITIC, as Research Center accredited by Galician University System, is funded by “Consellería de Cultura, Educación e Universidade from Xunta de Galicia”, supported in an 80% through ERDF Funds, ERDF Operational Programme Galicia 2014-2020, and the remaining 20% by “Secretaría Xeral de Universidades” (Grant ED431G 2019/01), Xunta de Galicia/FEDER-UE under Grants [IG240.2020.1.185; IN852A 2018/14] and Ministerio de Ciencia, Innovación under Grants [TIN2016-78011-C4-1-R; RTC-2017-5908-7]. For the Basque team: Ministerio de Ciencia, Innovación y Universidades under Grant [FEDER/TIN2016-78011-C4-2-R] and the Basque Government under Grant No. [IT1330-19]. Funding for open access charge: Universidade da Coruña/CISUG

Un sistema de tele-rehabilitación para personas mayores basado en Kinect

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Using Kinect to classify Parkinson's disease stages related to severity of gait impairment

Background: Parkinson’s Disease (PD) is a chronic neurodegenerative disease associated with motor problems such as gait impairment. Different systems based on 3D cameras, accelerometers or gyroscopes have been used in related works in order to study gait disturbances in PD. Kinect has also been used to build these kinds of systems, but contradictory results have been reported: some works conclude that Kinect does not provide an accurate method of measuring gait kinematics variables, but others, on the contrary, report good accuracy results. Methods: In this work, we have built a Kinect-based system that can distinguish between different PD stages, and have performed a clinical study with 30 patients suffering from PD belonging to three groups: early PD patients without axial impairment, more evolved PD patients with higher gait impairment but without Freezing of Gait (FoG), and patients with advanced PD and FoG. Those patients were recorded by two Kinect devices when they were walking in a hospital corridor. The datasets obtained from the Kinect were preprocessed, 115 features identified, some methods were applied to select the relevant features (correlation based feature selection, information gain, and consistency subset evaluation), and different classification methods (decision trees, Bayesian networks, neural networks and K-nearest neighbours classifiers) were evaluated with the goal of finding the most accurate method for PD stage classification. Results: The classifier that provided the best results is a particular case of a Bayesian Network classifier (similar to a Naïve Bayesian classifier) built from a set of 7 relevant features selected by the correlation-based on feature selection method. The accuracy obtained for that classifier using 10-fold cross validation is 93.40%. The relevant features are related to left shin angles, left humerus angles, frontal and lateral bents, left forearm angles and the number of steps during spin. Conclusions: In this paper, it is shown that using Kinect is adequate to build a inexpensive and comfortable system that classifies PD into three different stages related to FoG. Compared to the results of previous works, the obtained accuracy (93.40%) can be considered high. The relevant features for the classifier are: a) movement and position of the left arm, b) trunk position for slightly displaced walking sequences, and c) left shin angle, for straight walking sequences. However, we have obtained a better accuracy (96.23%) for a classifier that only uses features extracted from slightly displaced walking steps and spin walking steps. Finally, the obtained set of relevant features may lead to new rehabilitation therapies for PD patients with gait problems

Agent Applications in Tourism

Agent technology has been applied in recent years to solve different problems that are common to many applications in Tourism, such as dynamic service discovery, automatic management of user profiles, personalisation of cultural information or planning of touristic activities. This chapter shows different contributions of Spanish research groups in the following areas: personalised access to cultural information from mobile devices, planning of complex touristic activities, service discovery in Tourism applications and dynamic location tracking