Ontological approach to the knowledge systematization of a toxic process and toxic course representation framework for early drug risk management.

Sci Rep. 2020 Sep 03;10(1):14581

Authors: Yamagata Y, Yamada H

Abstract
Various types of drug toxicity can halt the development of a drug. Because drugs are xenobiotics, they inherently have the potential to cause injury. Clarifying the mechanisms of toxicity to evaluate and manage drug safety during drug development is extremely important. However, toxicity mechanisms, especially hepatotoxic mechanisms, are very complex. The significant exposure of liver cells to drugs can cause dysfunction, cell injury, and organ failure in the liver. To clarify potential risks in drug safety management, it is necessary to systematize knowledge from a consistent viewpoint. In this study, we adopt an ontological approach. Ontology provides a controlled vocabulary for sharing and reusing of various data with a computer-friendly manner. We focus on toxic processes, especially hepatotoxic processes, and construct the toxic process ontology (TXPO). The TXPO systematizes knowledge concerning hepatotoxic courses with consistency and no ambiguity. In our application study, we developed a toxic process interpretable knowledge system (TOXPILOT) to bridge the gaps between basic science and medicine for drug safety management. Using semantic web technology, TOXPILOT supports the interpretation of toxicity mechanisms and provides visualizations of toxic courses with useful information based on ontology. Our system will contribute to various applications for drug safety evaluation and management.

PMID: 32883995 [PubMed - in process]

Design and Use of Semantic Resources: Findings from the Section on Knowledge Representation and Management of the 2020 International Medical Informatics Association Yearbook.

Yearb Med Inform. 2020 Aug;29(1):163-168

Authors: Dhombres F, Charlet J, Section Editors for the IMIA Yearbook Section on Knowledge Representation and Management

Abstract
OBJECTIVE: To select, present, and summarize the best papers in the field of Knowledge Representation and Management (KRM) published in 2019.
METHODS: A comprehensive and standardized review of the biomedical informatics literature was performed to select the most interesting papers of KRM published in 2019, based on PubMed and ISI Web Of Knowledge queries.
RESULTS: Four best papers were selected among 1,189 publications retrieved, following the usual International Medical Informatics Association Yearbook reviewing process. In 2019, research areas covered by pre-selected papers were represented by the design of semantic resources (methods, visualization, curation) and the application of semantic representations for the integration/enrichment of biomedical data. Besides new ontologies and sound methodological guidance to rethink knowledge bases design, we observed large scale applications, promising results for phenotypes characterization, semantic-aware machine learning solutions for biomedical data analysis, and semantic provenance information representations for scientific reproducibility evaluation.
CONCLUSION: In the KRM selection for 2019, research on knowledge representation demonstrated significant contributions both in the design and in the application of semantic resources. Semantic representations serve a great variety of applications across many medical domains, with actionable results.

PMID: 32823311 [PubMed - as supplied by publisher]

Language and Speech Markers of Primary Progressive Aphasia: A Systematic Review.

Am J Speech Lang Pathol. 2020 Aug 18;:1-20

Authors: Stalpaert J, Cocquyt EM, Criel Y, Segers L, Miatton M, Van Langenhove T, van Mierlo P, De Letter M

Abstract
Purpose This systematic review aimed to establish language and speech markers to support the clinical diagnosis of primary progressive aphasia (PPA) and its clinical phenotypes. Our first objective was to identify behavioral language and speech markers of early-stage PPA. Our second objective was to identify the electrophysiological correlates of the language and speech characteristics in PPA. Method The databases MEDLINE, Web of Science, and Embase were searched for relevant articles. To identify behavioral markers, the initial subjective complaints and the language and speech deficits detected during the initial diagnostic evaluation were summarized for PPA in general and each clinical variant according to the 2011 consensus diagnostic criteria (nonfluent variant [NFV], semantic variant, and logopenic variant [LV]). To identify electrophysiological markers, the studies in which event-related potentials (ERPs) were elicited by a language or speech paradigm in patients with PPA were included. Results In total, 114 relevant studies were identified, including 110 behavioral studies and only four electrophysiological studies. This review suggests that patients with the semantic variant could be accurately differentiated from the NFV and LV in the initial stages based on the consensus criteria. Nonetheless, the early differentiation between the NFV and LV is not straightforward. In the four electrophysiological studies, differences in the latency, amplitude, and topographical distribution of the semantic N400 component were found between patients with PPA and healthy controls. Conclusions To accurately differentiate the NFV from the LV, it could be important to assess the language and speech degeneration by more specific assessments and by more objective diagnostic methods that offer insights into the language-related processes. Electrophysiological markers of PPA were not identified in this review due to the low number of studies that investigated language-related ERPs. More controlled ERP studies in larger patient cohorts are needed to investigate the diagnostic applicability of language-related ERPs in PPA. Supplemental Material https://doi.org/10.23641/asha.12798080.

PMID: 32810414 [PubMed - as supplied by publisher]

COVID-19 outbreak: organisation of a geriatric assessment and coordination unit. A French example.

Age Ageing. 2020 07 01;49(4):516-522

Authors: Koeberle S, Tannou T, Bouiller K, Becoulet N, Outrey J, Chirouze C, Aubry R

Abstract
Older people are particularly affected by the COVID-19 outbreak because of their vulnerability as well as the complexity of health organisations, particularly in the often-compartmentalised interactions between community, hospital and nursing home actors. In this endemic situation, with massive flows of patients requiring holistic management including specific and intensive care, the appropriate assessment of each patient's level of care and the organisation of specific networks is essential. To that end, we propose here a territorial organisation of health care, favouring communication between all actors. This organisation of care is based on three key points: To use the basis of territorial organisation of health by facilitating the link between hospital settings and geriatric sectors at the regional level.To connect private, medico-social and hospital actors through a dedicated centralised unit for evaluation, geriatric coordination of care and decision support. A geriatrician coordinates this multidisciplinary unit. It includes an emergency room doctor, a supervisor from the medical regulation centre (Centre 15), an infectious disease physician, a medical hygienist and a palliative care specialist.To organise an ad hoc follow-up channel, including the necessary resources for the different levels of care required, according to the resources of the territorial network, and the creation of a specific COVID geriatric palliative care service. This organisation meets the urgent health needs of all stakeholders, facilitating its deployment and allows the sustainable implementation of a coordinated geriatric management dynamic between the stakeholders on the territory.

PMID: 32725209 [PubMed - indexed for MEDLINE]

Sentiment Analysis and Emotion Understanding during the COVID-19 Pandemic in Spain and Its Impact on Digital Ecosystems.

Int J Environ Res Public Health. 2020 Jul 31;17(15):

Authors: de Las Heras-Pedrosa C, Sánchez-Núñez P, Peláez JI

Abstract
COVID-19 has changed our lives forever. The world we knew until now has been transformed and nowadays we live in a completely new scenario in a perpetual restructuring transition, in which the way we live, relate, and communicate with others has been altered permanently. Within this context, risk communication is playing a decisive role when informing, transmitting, and channeling the flow of information in society. COVID-19 has posed a real pandemic risk management challenge in terms of impact, preparedness, response, and mitigation by governments, health organizations, non-governmental organizations (NGOs), mass media, and stakeholders. In this study, we monitored the digital ecosystems during March and April 2020, and we obtained a sample of 106,261 communications through the analysis of APIs and Web Scraping techniques. This study examines how social media has affected risk communication in uncertain contexts and its impact on the emotions and sentiments derived from the semantic analysis in Spanish society during the COVID-19 pandemic.

PMID: 32751866 [PubMed - in process]

Knowledge Graph Approach to Combustion Chemistry and Interoperability.

ACS Omega. 2020 Jul 28;5(29):18342-18348

Authors: Farazi F, Salamanca M, Mosbach S, Akroyd J, Eibeck A, Aditya LK, Chadzynski A, Pan K, Zhou X, Zhang S, Lim MQ, Kraft M

Abstract
In this paper, we demonstrate through examples how the concept of a Semantic Web based knowledge graph can be used to integrate combustion modeling into cross-disciplinary applications and in particular how inconsistency issues in chemical mechanisms can be addressed. We discuss the advantages of linked data that form the essence of a knowledge graph and how we implement this in a number of interconnected ontologies, specifically in the context of combustion chemistry. Central to this is OntoKin, an ontology we have developed for capturing both the content and the semantics of chemical kinetic reaction mechanisms. OntoKin is used to represent the example mechanisms from the literature in a knowledge graph, which itself is part of the existing, more general knowledge graph and ecosystem of autonomous software agents that are acting on it. We describe a web interface, which allows users to interact with the system, upload and compare the existing mechanisms, and query species and reactions across the knowledge graph. The utility of the knowledge-graph approach is demonstrated for two use-cases: querying across multiple mechanisms from the literature and modeling the atmospheric dispersion of pollutants emitted by ships. As part of the query use-case, our ontological tools are applied to identify variations in the rate of a hydrogen abstraction reaction from methane as represented by 10 different mechanisms.

PMID: 32743209 [PubMed]

PyramidTags: Context-, Time- and Word Order-Aware Tag Maps to Explore Large Document Collections.

IEEE Trans Vis Comput Graph. 2020 Jul 17;PP:

Authors: Knittel J, Koch S, Ertl T

Abstract
It is difficult to explore large text collections if no or little information is available on the contained documents. Hence, starting analytic tasks on such corpora is challenging for many stakeholders from various domains. As a remedy, recent visualization research suggests to use visual spatializations of representative text documents or tags to explore text collections. With PyramidTags, we introduce a novel approach for summarizing large text collections visually. In contrast to previous work, PyramidTags in particular aims at creating an improved representation that incorporates both temporal evolution and semantic relationship of visualized tags within the summarized document collection. As a result, it equips analysts with a visual starting point for interactive exploration to not only get an overview of the main terms and phrases of the corpus, but also to grasp important ideas and stories. Analysts can hover and select multiple tags to explore relationships and retrieve the most relevant documents. In this work, we apply PyramidTags to hundreds of thousands of web-crawled news reports. Our benchmarks suggest that PyramidTags creates time- and context-aware layouts, while preserving the inherent word order of important pairs.

PMID: 32746277 [PubMed - as supplied by publisher]

Translation and Validation of the Caffeine Expectancy Questionnaire in Brazil (CaffEQ-BR).

Nutrients. 2020 Jul 28;12(8):

Authors: Mendes GF, Reis CEG, Nakano EY, da Costa THM, Saunders B, Zandonadi RP

Abstract
Caffeine is the world's most commonly used stimulant of the central nervous system. Caffeine is present in coffee and other beverages such as tea, soft drinks, and cocoa-based foods. The caffeine expectancy questionnaire was developed to investigate the effects of caffeine expectations and thus contribute to knowledge about its usage and subjective effects (response expectancies). This study aimed to evaluate caffeine expectation psychometrically in a sample of the Brazilian population. The original version of the "Caffeine Expectancy Questionnaire (CaffEQ)" was translated and validated into Brazilian-Portuguese and adapted to Brazilian culture to be used in the Brazilian adult (19-59 y) population. After the translation and back-translation processes of the original CaffEQ questionnaire, the content and semantic validation were performed by a group of experts. The Brazilian-Portuguese version of the questionnaire consists of 47 items, in seven factors, which assess subjective perceptions about the effects of caffeine. Interobserver reproducibility and internal consistency of the questionnaire were tested with a convenience sample (n = 50) of Brazilian adult consumers of caffeine sources, who completed the Brazilian CaffEQ (CaffEQ-BR) on two occasions separated by 24 h. All of the 47 questions were adequate regarding reliability, clarity, and comprehension. Psychometric properties could be replicated consistently. Appropriate internal consistency and validation were confirmed by Cronbach's alpha (α) 0.948, and an intraclass correlation coefficient of 0.976 was observed. The CaffEQ-BR was applied using a web-based platform to a convenience sample of Brazilian adults from all 27 Brazilian states (n = 4202 participants), along with measures of sociodemographic and caffeine consumption data. Factor validity was verified by confirmatory factor analysis. The seven factors presented a good fit for Root Mean Square Error of Approximation-RMSEA = 0.0332 (95% CI: 0.0290-0.0375). By confirming the validity and reliability of CaffEQ-BR, a useful tool is now available to assess caffeine expectations in the Brazilian adult population.

PMID: 32731330 [PubMed - in process]

Self-harm presentation across healthcare settings by sex in young people: an e-cohort study using routinely collected linked healthcare data in Wales, UK.

Arch Dis Child. 2020 04;105(4):347-354

Authors: Marchant A, Turner S, Balbuena L, Peters E, Williams D, Lloyd K, Lyons R, John A

Abstract
BACKGROUND: This study used individual-level linked data across general practice, emergency departments (EDs), outpatients and hospital admissions to examine contacts across settings and time by sex for self-harm in individuals aged 10-24 years old in Wales, UK.
METHODS: A whole population-based e-cohort study of routinely collected healthcare data was conducted. Rates of self-harm across settings over time by sex were examined. Individuals were categorised based on the service(s) to which they presented.
RESULTS: A total of 937 697 individuals aged 10-24 years contributed 5 369 794 person years of data from 1 January 2003 to 30 September 2015. Self-harm incidence was highest in primary care but remained stable over time (incident rate ratio (IRR)=1.0; 95% CI 0.9 to 1.1). Incidence of ED attendance increased over time (IRR=1.3; 95% CI 1.2 to 1.5) as did hospital admissions (IRR=1.4; 95% CI 1.1 to 1.6). Incidence in the 15-19 years age group was the highest across all settings. The largest increases were seen in the youngest age group. There were increases in ED attendances for both sexes; however, females are more likely than males to be admitted following this. This was most evident in individuals 10-15 years old, where 76% of females were admitted compared with just 49% of males. The majority of associated outpatient appointments were under a mental health specialty.
CONCLUSIONS: This is the first study to compare self-harm in people aged 10-24 years across primary care, EDs and hospital settings in the UK. The high rates of self-harm in primary care and for young men in EDs highlight these as important settings for intervention.

PMID: 31611193 [PubMed - indexed for MEDLINE]

IDP-Seq2Seq: Identification of Intrinsically Disordered Regions based on Sequence to Sequence Learning.

Bioinformatics. 2020 Jul 23;:

Authors: Tang YJ, Pang YH, Liu B

Abstract
MOTIVATION: Related to many important biological functions, intrinsically disordered regions (IDRs) are widely distributed in proteins. Accurate prediction of intrinsically disordered regions is critical for the protein structure and function analysis. However, the existing computational methods construct the predictive models solely in the sequence space, failing to convert the sequence space into the "semantic space" to reflect the structure characteristics of proteins. Furthermore, although the length-dependent predictors showed promising results, new fusion strategies should be explored to improve their predictive performance and the generalization.
RESULTS: In this study, we applied the Sequence to Sequence Learning (Seq2Seq) derived from natural language processing (NLP) to map protein sequences to "semantic space" to reflect the structure patterns with the help of predicted Residue-Residue Contacts (CCMs) and other sequence-based features. Furthermore, the Attention mechanism was employed to capture the global associations between all residue pairs in the proteins. Three length-dependent predictors were constructed: IDP-Seq2Seq-L for long disordered region prediction, IDP-Seq2Seq-S for short disordered region prediction, and IDP-Seq2Seq-G for both long and short disordered region prediction. Finally, these three predictors were fused into one predictor called IDP-Seq2Seq to improve the discriminative power and generalization. Experimental results on four independent test datasets and the CASP test dataset showed that IDP-Seq2Seq is insensitive with the ratios of long and short disordered regions and outperforms other competing methods.
AVAILABILITY: For the convenience of most experimental scientists, a user-friendly and publicly accessible web-server for the powerful new predictor has been established at http://bliulab.net/IDP-Seq2Seq/. It is anticipated that IDP-Seq2Seq will become a very useful tool for identification of intrinsically disordered regions.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID: 32702119 [PubMed - as supplied by publisher]

Dengue during pregnancy and live birth outcomes: a cohort of linked data from Brazil.

BMJ Open. 2019 07 24;9(7):e023529

Authors: Paixão ES, Campbell OM, Teixeira MG, Costa MC, Harron K, Barreto ML, Leal MB, Almeida MF, Rodrigues LC

Abstract
OBJECTIVES: Dengue is the most common viral mosquito-borne disease, and women of reproductive age who live in or travel to endemic areas are at risk. Little is known about the effects of dengue during pregnancy on birth outcomes. The objective of this study is to examine the effect of maternal dengue severity on live birth outcomes.
DESIGN AND SETTING: We conducted a population-based cohort study using routinely collected Brazilian data from 2006 to 2012.
PARTICIPATING: We linked birth registration records and dengue registration records to identify women with and without dengue during pregnancy. Using multinomial logistic regression and Firth method, we estimated risk and ORs for preterm birth (<37 weeks' gestation), low birth weight (<2500 g) and small for gestational age (<10thcentile). We also investigated the effect of time between the onset of the disease and each outcome.
RESULTS: We included 16 738 000 live births. Dengue haemorrhagic fever was associated with preterm birth (OR=2.4; 95% CI 1.3 to 4.4) and low birth weight (OR=2.1; 95% CI 1.1 to 4.0), but there was no evidence of effect for small for gestational age (OR=2.1; 95% CI 0.4 to 12.2). The magnitude of the effects was higher in the acute disease period.
CONCLUSION: This study showed an increased risk of adverse birth outcomes in women with severe dengue during pregnancy. Medical intervention to mitigate maternal risk during severe acute dengue episodes may improve outcomes for infants born to exposed mothers.

PMID: 31345962 [PubMed - indexed for MEDLINE]

A knowledge-based system to find over-the-counter medicines for self-medication.

J Biomed Inform. 2020 Jul 13;:103504

Authors: Sung HY, Chi YL

Abstract
This study developed a medicine query system based on Semantic Web and open data especially for self-medication users to search over-the-counter (OTC) medicines. Most existing medicine query systems are based on keyword searches. If users are uncertain about the exact search words, these query systems do not offer effective help. Furthermore, most systems provide inadequate explanations of symptoms and ailments for users to use with confidence. To remedy these issues, this study builds a knowledge base to enable inference-based searches and data mashup for integrating information from across the Web. Three components were identified: (1) building an ontology model to describe the relationships between ailments and symptoms; (2) upgrading medicinal product datasets to link them with the ontology model on a semantic level; and (3) developing a data mashup to integrate web resources to help users to find references. Furthermore, the aim was to develop a web-based application that utilizes inference mechanisms to provide users with tools for interactive manipulation. A pilot experiment for skin ailments was implemented to learn the problem-solving skills of the system. Finally, two experts utilized a content validity index to rate a four-dimension 15-item scale. The evaluation results show that experts found the proposed system excellent for content validity.

PMID: 32673790 [PubMed - as supplied by publisher]

Reflections on modern methods: linkage error bias.

Int J Epidemiol. 2019 12 01;48(6):2050-2060

Authors: Doidge JC, Harron KL

Abstract
Linked data are increasingly being used for epidemiological research, to enhance primary research, and in planning, monitoring and evaluating public policy and services. Linkage error (missed links between records that relate to the same person or false links between unrelated records) can manifest in many ways: as missing data, measurement error and misclassification, unrepresentative sampling, or as a special combination of these that is specific to analysis of linked data: the merging and splitting of people that can occur when two hospital admission records are counted as one person admitted twice if linked and two people admitted once if not. Through these mechanisms, linkage error can ultimately lead to information bias and selection bias; so identifying relevant mechanisms is key in quantitative bias analysis. In this article we introduce five key concepts and a study classification system for identifying which mechanisms are relevant to any given analysis. We provide examples and discuss options for estimating parameters for bias analysis. This conceptual framework provides the 'links' between linkage error, information bias and selection bias, and lays the groundwork for quantitative bias analysis for linkage error.

PMID: 31633184 [PubMed - indexed for MEDLINE]

A scientometric analysis of birth cohorts in South Asia: Way forward for Pakistan.

PLoS One. 2020;15(7):e0235385

Authors: Waqas A, Zafar S, Lawlor DA, Wright J, Hafeez A, Ahmad I, Sikander S, Rahman A

Abstract
The present study aims to: a) systematically map the of birth cohort studies from the South Asian region b) examine the major research foci and landmark contributions from these cohorts using reproducible scientometric techniques and c) offer recommendations on establishing new birth cohorts in Pakistan, building upon the strengths, weaknesses and gaps of previous cohorts. Bibliographic records for a total of 260 articles, published during through December 2018, were retrieved from the Web of Science (core database). All data were analysed using Microsoft Excel (2013), Web of Science platform and CiteSpace. A series of network analysis were then run for each time-period using the link reduction method and pathfinder network scaling. The co-cited articles were clustered into their homogeneous research clusters. The clusters were named using the Latent Semantic Indexing (LSI) method that utilized author keywords as source of names for these clusters. The scientometric analyses of original research output from these birth cohorts also paint a pessimistic landscape in Pakistan- where Pakistani sites for birth cohorts contributed only 31 publications; a majority of these utilized the MAL-ED birth cohort data. A majority of original studies were published from birth cohorts in India (156), Bangladesh (63), and Nepal (15). Out of these contributions, 31 studies reported data from multiple countries. The three major birth cohorts include prospective and multi-country MAL-ED birth cohort and The Pakistan Early Childhood Development Scale Up Trial, and a retrospective Maternal and infant nutrition intervention cohort. In addition to these, a few small-scale birth cohorts reported findings pertaining to neonatal sepsis, intrauterine growth retardation and its effects on linear growth of children and environmental enteropathy.

PMID: 32645067 [PubMed - as supplied by publisher]

Enabling ad-hoc reuse of private data repositories through schema extraction.

J Biomed Semantics. 2020 Jul 08;11(1):6

Authors: Gleim LC, Karim MR, Zimmermann L, Kohlbacher O, Stenzhorn H, Decker S, Beyan O

Abstract
BACKGROUND: Sharing sensitive data across organizational boundaries is often significantly limited by legal and ethical restrictions. Regulations such as the EU General Data Protection Rules (GDPR) impose strict requirements concerning the protection of personal and privacy sensitive data. Therefore new approaches, such as the Personal Health Train initiative, are emerging to utilize data right in their original repositories, circumventing the need to transfer data.
RESULTS: Circumventing limitations of previous systems, this paper proposes a configurable and automated schema extraction and publishing approach, which enables ad-hoc SPARQL query formulation against RDF triple stores without requiring direct access to the private data. The approach is compatible with existing Semantic Web-based technologies and allows for the subsequent execution of such queries in a safe setting under the data provider's control. Evaluation with four distinct datasets shows that a configurable amount of concise and task-relevant schema, closely describing the structure of the underlying data, was derived, enabling the schema introspection-assisted authoring of SPARQL queries.
CONCLUSIONS: Automatically extracting and publishing data schema can enable the introspection-assisted creation of data selection and integration queries. In conjunction with the presented system architecture, this approach can enable reuse of data from private repositories and in settings where agreeing upon a shared schema and encoding a priori is infeasible. As such, it could provide an important step towards reuse of data from previously inaccessible sources and thus towards the proliferation of data-driven methods in the biomedical domain.

PMID: 32641124 [PubMed - in process]

CLIN-IK-LINKS: A platform for the design and execution of clinical data transformation and reasoning workflows.

Comput Methods Programs Biomed. 2020 Jun 25;197:105616

Authors: Maldonado JA, Marcos M, Fernández-Breis JT, Giménez-Solano VM, Legaz-García MDC, Martínez-Salvador B

Abstract
BACKGROUND AND OBJECTIVE: Effective sharing and reuse of Electronic Health Records (EHR) requires technological solutions which deal with different representations and different models of data. This includes information models, domain models and, ideally, inference models, which enable clinical decision support based on a knowledge base and facts. Our goal is to develop a framework to support EHR interoperability based on transformation and reasoning services intended for clinical data and knowledge.
METHODS: Our framework is based on workflows whose primary components are reusable mappings. Key features are an integrated representation, storage, and exploitation of different types of mappings for clinical data transformation purposes, as well as the support for the discovery of new workflows. The current framework supports mappings which take advantage of the best features of EHR standards and ontologies. Our proposal is based on our previous results and experience working with both technological infrastructures.
RESULTS: We have implemented CLIN-IK-LINKS, a web-based platform that enables users to create, modify and delete mappings as well as to define and execute workflows. The platform has been applied in two use cases: semantic publishing of clinical laboratory test results; and implementation of two colorectal cancer screening protocols. Real data have been used in both use cases.
CONCLUSIONS: The CLIN-IK-LINKS platform allows the composition and execution of clinical data transformation workflows to convert EHR data into EHR and/or semantic web standards. Having proved its usefulness to implement clinical data transformation applications of interest, CLIN-IK-LINKS can be regarded as a valuable contribution to improve the semantic interoperability of EHR systems.

PMID: 32629294 [PubMed - as supplied by publisher]

Data Integration in the Brazilian Public Health System for Tuberculosis: Use of the Semantic Web to Establish Interoperability.

JMIR Med Inform. 2020 Jul 06;8(7):e17176

Authors: Pellison FC, Rijo RPCL, Lima VC, Crepaldi NY, Bernardi FA, Galliez RM, Kritski A, Abhishek K, Alves D

Abstract
BACKGROUND: Interoperability of health information systems is a challenge due to the heterogeneity of existing systems at both the technological and semantic levels of their data. The lack of existing data about interoperability disrupts intra-unit and inter-unit medical operations as well as creates challenges in conducting studies on existing data. The goal is to exchange data while providing the same meaning for data from different sources.
OBJECTIVE: To find ways to solve this challenge, this research paper proposes an interoperability solution for the tuberculosis treatment and follow-up scenario in Brazil using Semantic Web technology supported by an ontology.
METHODS: The entities of the ontology were allocated under the definitions of Basic Formal Ontology. Brazilian tuberculosis applications were tagged with entities from the resulting ontology.
RESULTS: An interoperability layer was developed to retrieve data with the same meaning and in a structured way enabling semantic and functional interoperability.
CONCLUSIONS: Health professionals could use the data gathered from several data sources to enhance the effectiveness of their actions and decisions, as shown in a practical use case to integrate tuberculosis data in the State of São Paulo.

PMID: 32628611 [PubMed - as supplied by publisher]

A hands-on introduction to querying evolutionary relationships across multiple data sources using SPARQL.

F1000Res. 2019;8:1822

Authors: Sima AC, Dessimoz C, Stockinger K, Zahn-Zabal M, Mendes de Farias T

Abstract
The increasing use of Semantic Web technologies in the life sciences, in particular the use of the Resource Description Framework (RDF) and the RDF query language SPARQL, opens the path for novel integrative analyses, combining information from multiple sources. However, analyzing evolutionary data in RDF is not trivial, due to the steep learning curve required to understand both the data models adopted by different RDF data sources, as well as the SPARQL query language. In this article, we provide a hands-on introduction to querying evolutionary data across multiple sources that publish orthology information in RDF, namely: The Orthologous MAtrix (OMA), the European Bioinformatics Institute (EBI) RDF platform, the Database of Orthologous Groups (OrthoDB) and the Microbial Genome Database (MBGD). We present four protocols in increasing order of complexity. In these protocols, we demonstrate through SPARQL queries how to retrieve pairwise orthologs, homologous groups, and hierarchical orthologous groups. Finally, we show how orthology information in different sources can be compared, through the use of federated SPARQL queries.

PMID: 32612807 [PubMed - in process]

Semantic Web of Things (SWoT) for Global Infectious Disease Control and Prevention.

Stud Health Technol Inform. 2020 Jun 26;272:425-428

Authors: Shaban-Nejad A, Brenas JH, Al Manir MS, Zinszer K, Baker CJO

Abstract
This paper reports on the early-stage development of an analytics framework to support the semantic integration of dynamic surveillance data across multiple scales to inform decision making for malaria eradication. We propose using the Semantic Web of Things (SWoT), a combination of Internet of Things (IoT) and semantic web technologies, to support the evolution and integration of dynamic malaria data sources and improve interoperability between different datasets generated through relevant IoT assets (e.g. computers, sensors, persons, and other smart objects and devices).

PMID: 32604693 [PubMed - in process]

Towards an Architecture for the Interoperability of Hospital Information Systems in Burkina Faso.

Stud Health Technol Inform. 2020 Jun 26;272:159-162

Authors: Tapsoba LS, Traore Y, Malo S

Abstract
The successful introduction of ICTs into medical practice is a key factor in improving the performance of any health system for both patients and healthcare professionals. In Burkina Faso, many hospital information systems (HIS) have been developed and are already widely used in large health centers with proven efficiency. To improve the quality of patient care, these hospital information systems should exchange information. Interoperability is one of the privileged ways to improve the integration of different systems because nowadays a HIS is no longer just a single monolithic software system, which is run on a single machine. This paper presents a semantic interoperability architecture, which is based on a mediation approach. The mediator implements local domain ontologies for each HIS, a knowledge base, and a referential ontology which is used as a semantic repository and web services.

PMID: 32604625 [PubMed - in process]