Lightweight Data-Security Ontology for IoT.

Sensors (Basel). 2020 Feb 01;20(3):

Authors: Gonzalez-Gil P, Martinez JA, Skarmeta AF

Abstract
Although current estimates depict steady growth in Internet of Things (IoT), many works portray an as yet immature technology in terms of security. Attacks using low performance devices, the application of new technologies and data analysis to infer private data, lack of development in some aspects of security offer a wide field for improvement. The advent of Semantic Technologies for IoT offers a new set of possibilities and challenges, like data markets, aggregators, processors and search engines, which rise the need for security. New regulations, such as GDPR , also call for novel approaches on data-security, covering personal data. In this work, we present DS4IoT, a data-security ontology for IoT, which covers the representation of data-security concepts with the novel approach of doing so from the perspective of data and introducing some new concepts such as regulations, certifications and provenance, to classical concepts such as access control methods and authentication mechanisms. In the process we followed ontological methodologies, as well as semantic web best practices, resulting in an ontology to serve as a common vocabulary for data annotation that not only distinguishes itself from previous works by its bottom-up approach, but covers new, current and interesting concepts of data-security, favouring implicit over explicit knowledge representation. Finally, this work is validated by proof of concept, by mapping the DS4IoT ontology to the NGSI-LD data model, in the frame of the IoTCrawler EU project.

PMID: 32024127 [PubMed - in process]

Patient and Kidney Allograft Survival with National Kidney Paired Donation.

Clin J Am Soc Nephrol. 2020 Jan 28;:

Authors: Leeser DB, Thomas AG, Shaffer AA, Veale JL, Massie AB, Cooper M, Kapur S, Turgeon N, Segev DL, Waterman AD, Flechner SM

Abstract
BACKGROUND AND OBJECTIVES: In the United States, kidney paired donation networks have facilitated an increasing proportion of kidney transplants annually, but transplant outcome differences beyond 5 years between paired donation and other living donor kidney transplant recipients have not been well described.
DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Using registry-linked data, we compared National Kidney Registry (n=2363) recipients to control kidney transplant recipients (n=54,497) (February 2008 to December 2017). We estimated the risk of death-censored graft failure and mortality using inverse probability of treatment weighted Cox regression. The parsimonious model adjusted for recipient factors (age, sex, black, race, body mass index ≥30 kg/m2, diabetes, previous transplant, preemptive transplant, public insurance, hepatitis C, eGFR, antibody depleting induction therapy, year of transplant), donor factors (age, sex, Hispanic ethnicity, body mass index ≥30 kg/m2), and transplant factors (zero HLA mismatch).
RESULTS: National Kidney Registry recipients were more likely to be women, black, older, on public insurance, have panel reactive antibodies >80%, spend longer on dialysis, and be previous transplant recipients. National Kidney Registry recipients were followed for a median 3.7 years (interquartile range, 2.1-5.6; maximum 10.9 years). National Kidney Registry recipients had similar graft failure (5% versus 6%; log-rank P=0.2) and mortality (9% versus 10%; log-rank P=0.4) incidence compared with controls during follow-up. After adjustment for donor, recipient, and transplant factors, there no detectable difference in graft failure (adjusted hazard ratio, 0.95; 95% confidence interval, 0.77 to 1.18; P=0.6) or mortality (adjusted hazard ratio, 0.86; 95% confidence interval, 0.70 to 1.07; P=0.2) between National Kidney Registry and control recipients.
CONCLUSIONS: Even after transplanting patients with greater risk factors for worse post-transplant outcomes, nationalized paired donation results in equivalent outcomes when compared with control living donor kidney transplant recipients.

PMID: 31992572 [PubMed - as supplied by publisher]

Dataset of ontology competency questions to SPARQL-OWL queries translations.

Data Brief. 2020 Apr;29:105098

Authors: Potoniec J, Wiśniewski D, Ławrynowicz A, Keet CM

Abstract
This data article reports on a new set of 234 competency questions for ontology development and their formalisation into a set of 131 SPARQL-OWL queries. This is the largest set of competency questions with their linked queries to date, covering several ontologies of different type in different subject domains developed by different groups of question authors and ontology developers. The dataset is focused specifically on the ontology TBox (terminological part). The dataset may serve as a manually created gold standard for testing and benchmarking, research into competency questions and querying ontologies, and tool development. The data is available in Mendeley Data. Its analysis is presented in "Analysis of Ontology Competency Questions and their formalizations in SPARQL-OWL" [15].

PMID: 31989008 [PubMed]

Explaining an Influential Model of the Significant Relationship Between Religion, Spirituality, and Environmental Peace in Mosque Interior Architecture.

J Relig Health. 2020 Jan 21;:

Authors: MahdiNejad JE, Azemati H, Sadeghi Habibabad A

Abstract
Investigating the components of environmental peace in an architectural work, especially Islamic mosques, requires a detailed understanding of this concept and its influential factors. In the architecture of the mosques of the past, certain patterns have always followed a continuous trend that made a logical relationship with the time before and after, but this continuity and trend are not seen today. The purpose of this study was to investigate the relationship of environmental peace from two aspects of religion and spirituality. Religion means comprehensive instructions and complete guidelines that, on the one hand, show the goal and teaches the human being how to achieve it, and on the other hand, help the human being on problems that are difficult to understand by universal means of understanding (reason, experience, and intuition). Therefore, the identification of the true ultimate goal in human life as well as the determination of the intermediate goals that indicate the path to the ultimate goal is possible only through the recognition and adherence to the right religion, and this fact shows the close relationship between religion and spirituality. The research method investigates the relationship between variables through a correlation method and then through structural equations. The statistical population was selected based on the Cochran formula including 120 professors and postgraduate students in architecture and Islamic architecture of Tehran Universities. The research tool was a web-based questionnaire and its link was made available to the statistical community online. The structural equation method was used in SPSS and Amos software to test the regression and fitting test model. Pearson correlation test was also used to determine the relationship between research variables. The results show that the model of the influence of "religion" factors in enhancing "environmental peace" through the mediating variable of "spirituality" explains these relationships; in other words, in this indirect causal relation, enhancement of semantic factors mediated by "spirituality" factors enhances environmental peace in architecture.

PMID: 31965465 [PubMed - as supplied by publisher]

Effect of cochlear implantation on language development and assessment of the quality of studies in this field: A systematic review.

Med J Islam Repub Iran. 2019;33:107

Authors: Khoramian S, Soleymani Z, Keramati N, Motasaddi Zarandy M

Abstract
Background: Cochlear implantation (CI) is an achievement that facilitates the acquisition of language skills in deaf children throughout the world. The use of this technology has a positive effect on all components of language acquisition (syntax, semantic, pragmatic, etc.). However, this positive impact is influenced by various factors. Understanding the strengths and weaknesses of studies on the development of language abilities can help improve these studies. Consequently, in the future, it will lead to the improvement of language rehabilitation in these children. Limited studies on children with CI in have been done so far. This article summarized the outcomes of scientific articles on the clinical efficacy of CI on Persian speaking children. This study also provided a clear picture of these studies by examining the quality of their methodologies and tools. Methods: Articles indexed in Google Scholar, Web of Science, Medline, Scopus and Iranian databases (Danesh Gostar, Magiran, and SID) were searched using keywords "language," "Cochlear implant", "Persian/ Farsi" in English and Persian languages with "and/or". Original articles investigated on children younger than 13 years old with hearing impairment and CI were included. Results: Five hundred and twenty-three articles were found based on the keywords. Among all of these, 485 were excluded due to the title and the abstract; we selected 38, of which 24 were repeated. Finally, 14 articles remained. We reviewed the articles based on the preferred reporting items for systematic review and meta-analysis (PRISMA) and checklist and Grading of Recommendations, Assessment, Development, and Evaluations (GRADE). Conclusion: Similar to international studies, Persian speaking children with CI have slower language development than their peers with normal hearing, but they are better than their peers who use hearing aids. The results of reviewing on quality of the articles showed that the studies could not meet reasonable quality because of the lack of a standard test in different aspects of Persian language and the absence of patients' databanks. These results also can be used by other nationalities that recently have started surveys on children with CIs.

PMID: 31934567 [PubMed]

Comprenhensive analysis of rule formalisms to represent clinical guidelines: Selection criteria and case study on antibiotic clinical guidelines.

Artif Intell Med. 2020 Jan 09;:101741

Authors: Iglesias N, Juarez JM, Campos M

Abstract
BACKGROUND: The over-use of antibiotics in clinical domains is causing an alarming increase in bacterial resistance, thus endangering their effectiveness as regards the treatment of highly recurring severe infectious diseases. Whilst Clinical Guidelines (CGs) focus on the correct prescription of antibiotics in a narrative form, Clinical Decision Support Systems (CDSS) operationalize the knowledge contained in CGs in the form of rules at the point of care. Despite the efforts made to computerize CGs, there is still a gap between CGs and the myriad of rule technologies (based on different logic formalisms) that are available to implement CDSSs in real clinical settings.
OBJECTIVE: To helpCDSS designers to determine the most suitable rule-based technology (medical-oriented rules, production rules and semantic web rules) with which to model knowledge from CGs for the prescription of antibiotics. We propose a framework of criteria for this purpose that is extensible to more generic CGs.
MATERIALS AND METHODS: Our proposal is based on the identification of core technical requirements extracted from both literature and the analysis of CGs for antibiotics, establishing three dimensions for analysis: language expressivity, interoperability and industrial aspects. We present a case study regarding the John Hopkins Hospital (JHH) Antibiotic Guidelines for Urinary Tract Infection (UTI), a highly recurring hospital acquired infection. We have adopted our framework of criteria in order to analyse and implement these CGs using various rule technologies: HL7 Arden Syntax, general-purpose Production Rules System (Drools), HL7 standard Rule Interchange Format (RIF), Semantic Web Rule Language (SWRL) and SParql Inference Notation (SPIN) rule extensions (implementing our own ontology for UTI).
RESULTS: We have identified the main criteria required to attain a maintainable and cost-affordable computable knowledge representation for CGs. We have represented the JHH UTI CGs knowledge in a total of 12 Arden Syntax MLMs, 81 Drools rules and 154 ontology classes, properties and individuals. Our experiments confirm the relevance of the proposed set of criteria and show the level of compliance of the different rule technologies with the JHH UTI CGs knowledge representation.
CONCLUSIONS: The proposed framework of criteria may help clinical institutions to select the most suitable rule technology for the representation of CGs in general, and for the antibiotic prescription domain in particular, depicting the main aspects that lead to Computer Interpretable Guidelines (CIGs), such as Logic expressivity (Open/Closed World Assumption, Negation-As-Failure), Temporal Reasoning and Interoperability with existing HIS and clinical workflow. Future work will focus on providing clinicians with suggestions regarding new potential steps for CGs, considering process mining approaches and CGs Process Workflows, the use of HL7 FHIR for HIS interoperability and the representation of Knowledge-as- a-Service (KaaS).

PMID: 31928849 [PubMed - as supplied by publisher]

STAT: A Web-based Semantic Text Annotation Tool to Assist Building Mental Health Knowledge Base.

IEEE Int Conf Healthc Inform. 2019 Jun;2019:

Authors: He X, Zhang H, Yang X, Guo Y, Bian J

Abstract
Mental health problems are serious among American adults and many of them are turning to the Internet for help. However, online mental health information is not well-organized and in low quality. We are building a mental health knowledge base (MHKB) with evidence-based information extracted from scientific literature manually, but lacking efficiency. We envision to leverage collective wisdoms through crowdsourcing to speed up the curation of MHKB. In order to integrate with crowdsourcing platforms, we designed and prototyped a web-based annotation tool, STAT (Semantic Text Annotation Tool), with real-time annotation recommendation and annotation quality analysis, to facilitate management of laypeople annotators recruited through crowdsourcing to complete the necessary annotation tasks.

PMID: 31903451 [PubMed]

A literature review of current technologies on health data integration for patient-centered health management.

Health Informatics J. 2019 Dec 30;:1460458219892387

Authors: Peng C, Goswami P, Bai G

Abstract
Health data integration enables a collaborative utilization of data across different systems. It not only provides a comprehensive view of a patient's health but can also potentially cope with challenges faced by the current healthcare system. In this literature review, we investigated the existing work on heterogeneous health data integration as well as the methods of utilizing the integrated health data. Our search was narrowed down to 32 articles for analysis. The integration approaches in the reviewed articles were classified into three classifications, and the utilization approaches were classified into five classifications. The topic of health data integration is still under debate and problems are far from being resolved. This review suggests the need for a more efficient way to invoke the various services for aggregating health data, as well as a more effective way to integrate the aggregated health data for supporting collaborative utilization. We have found that the combination of Web Application Programming Interface and Semantic Web technologies has the potential to cope with the challenges based on our analysis of the review result.

PMID: 31884843 [PubMed - as supplied by publisher]

Spelling performance on the web and in the lab.

PLoS One. 2019;14(12):e0226647

Authors: Rey A, Manguin JL, Olivier C, Pacton S, Courrieu P

Abstract
Several dictionary websites are available on the web to access semantic, synonymous, or spelling information about a given word. During nine years, we systematically recorded all the entered letter sequences from a French web dictionary. A total of 200 million orthographic forms were obtained allowing us to create a large-scale database of spelling errors that could inform psychological theories about spelling processes. To check the reliability of this big data methodology, we selected from this database a sample of 100 frequently misspelled words. A group of 100 French university students had to perform a spelling-to-dictation test on this list of words. The results showed a strong correlation between the two data sets on the frequencies of produced spellings (r = 0.82). Although the distributions of spelling errors were relatively consistent across the two databases, the proportion of correct responses revealed significant differences. Regression analyses allowed us to generate possible explanations for these differences in terms of task-dependent factors. We argue that comparing the results of these large-scale databases with those of standard and controlled experimental paradigms is certainly a good way to determine the conditions under which this big data methodology can be adequately used for informing psychological theories.

PMID: 31856230 [PubMed - in process]

The Lancaster Sensorimotor Norms: multidimensional measures of perceptual and action strength for 40,000 English words.

Behav Res Methods. 2019 Dec 12;:

Authors: Lynott D, Connell L, Brysbaert M, Brand J, Carney J

Abstract
Sensorimotor information plays a fundamental role in cognition. However, the existing materials that measure the sensorimotor basis of word meanings and concepts have been restricted in terms of their sample size and breadth of sensorimotor experience. Here we present norms of sensorimotor strength for 39,707 concepts across six perceptual modalities (touch, hearing, smell, taste, vision, and interoception) and five action effectors (mouth/throat, hand/arm, foot/leg, head excluding mouth/throat, and torso), gathered from a total of 3,500 individual participants using Amazon's Mechanical Turk platform. The Lancaster Sensorimotor Norms are unique and innovative in a number of respects: They represent the largest-ever set of semantic norms for English, at 40,000 words × 11 dimensions (plus several informative cross-dimensional variables), they extend perceptual strength norming to the new modality of interoception, and they include the first norming of action strength across separate bodily effectors. In the first study, we describe the data collection procedures, provide summary descriptives of the dataset, and interpret the relations observed between sensorimotor dimensions. We then report two further studies, in which we (1) extracted an optimal single-variable composite of the 11-dimension sensorimotor profile (Minkowski 3 strength) and (2) demonstrated the utility of both perceptual and action strength in facilitating lexical decision times and accuracy in two separate datasets. These norms provide a valuable resource to researchers in diverse areas, including psycholinguistics, grounded cognition, cognitive semantics, knowledge representation, machine learning, and big-data approaches to the analysis of language and conceptual representations. The data are accessible via the Open Science Framework (http://osf.io/7emr6/) and an interactive web application (https://www.lancaster.ac.uk/psychology/lsnorms/).

PMID: 31832879 [PubMed - as supplied by publisher]

Analysing the Scientific Publications of Peter Reichertz: Reflections from the Perspective of Medical Informatics Knowledge Today.

J Med Syst. 2019 Dec 11;44(1):23

Authors: Haux R

Abstract
Professor Peter L. Reichertz is one of the most significant pioneers in the field of medical informatics worldwide. In 1969, 50 years ago, he became Professor at the Hannover Medical School. On the occasion of this anniversary an attempt was made to report on the scientific work of Peter Reichertz and to reflect on this work in the light of medical informatics knowledge today. The aim of this study was to search publications listings in the Peter L. Reichertz Archive, in Pubmed/Medline, and in the Web of Science. As well as to analyse contents and communication approaches to help in classifying Peter Reichertz's scientific publications. Three comprehensive publication lists were identified: the Print Bibliography (384 publications), the Disc Bibliography (285 publications) and the Selected Publications Bibliography (111 publications). Based on the last bibliography, a classification was built along the semantic dimensions of (1) major topics, (2) fields of publication, and (3) publication languages. Major contents of Peter Reichertz's research in informatics were medical informatics as a field (including education), informatics applications in medicine and health care, and health information systems. Clear shifts over time were observed. To his research on informatics applications, in the 1970s health information systems was added as topic, which then became a major part of his research. While in the 1960s and earlier German was a major publication language, from the 1970s onwards this shifted to English as the major language. Peter Reichertz very early identified the potential of computers in medicine and health care. He did not just use information and communication technology and information processing methodology as if they were other technology, such as microscopes or ultrasonic devices, for improving diagnosis and therapy. He was visionary enough to very early see the revolutionary potential of informatics for biomedicine and health care, with consequential impact on research and education.

PMID: 31828547 [PubMed - in process]

Detecting Lifestyle Risk Factors for Chronic Kidney Disease With Comorbidities: Association Rule Mining Analysis of Web-Based Survey Data.

J Med Internet Res. 2019 Dec 10;21(12):e14204

Authors: Peng S, Shen F, Wen A, Wang L, Fan Y, Liu X, Liu H

Abstract
BACKGROUND: The rise in the number of patients with chronic kidney disease (CKD) and consequent end-stage renal disease necessitating renal replacement therapy has placed a significant strain on health care. The rate of progression of CKD is influenced by both modifiable and unmodifiable risk factors. Identification of modifiable risk factors, such as lifestyle choices, is vital in informing strategies toward renoprotection. Modification of unhealthy lifestyle choices lessens the risk of CKD progression and associated comorbidities, although the lifestyle risk factors and modification strategies may vary with different comorbidities (eg, diabetes, hypertension). However, there are limited studies on suitable lifestyle interventions for CKD patients with comorbidities.
OBJECTIVE: The objectives of our study are to (1) identify the lifestyle risk factors for CKD with common comorbid chronic conditions using a US nationwide survey in combination with literature mining, and (2) demonstrate the potential effectiveness of association rule mining (ARM) analysis for the aforementioned task, which can be generalized for similar tasks associated with noncommunicable diseases (NCDs).
METHODS: We applied ARM to identify lifestyle risk factors for CKD progression with comorbidities (cardiovascular disease, chronic pulmonary disease, rheumatoid arthritis, diabetes, and cancer) using questionnaire data for 450,000 participants collected from the Behavioral Risk Factor Surveillance System (BRFSS) 2017. The BRFSS is a Web-based resource, which includes demographic information, chronic health conditions, fruit and vegetable consumption, and sugar- or salt-related behavior. To enrich the BRFSS questionnaire, the Semantic MEDLINE Database was also mined to identify lifestyle risk factors.
RESULTS: The results suggest that lifestyle modification for CKD varies among different comorbidities. For example, the lifestyle modification of CKD with cardiovascular disease needs to focus on increasing aerobic capacity by improving muscle strength or functional ability. For CKD patients with chronic pulmonary disease or rheumatoid arthritis, lifestyle modification should be high dietary fiber intake and participation in moderate-intensity exercise. Meanwhile, the management of CKD patients with diabetes focuses on exercise and weight loss predominantly.
CONCLUSIONS: We have demonstrated the use of ARM to identify lifestyle risk factors for CKD with common comorbid chronic conditions using data from BRFSS 2017. Our methods can be generalized to advance chronic disease management with more focused and optimized lifestyle modification of NCDs.

PMID: 31821152 [PubMed - in process]

Association of Patient Treatment Preference With Dropout and Clinical Outcomes in Adult Psychosocial Mental Health Interventions: A Systematic Review and Meta-analysis.

JAMA Psychiatry. 2019 Dec 04;:

Authors: Windle E, Tee H, Sabitova A, Jovanovic N, Priebe S, Carr C

Abstract
Importance: Receiving a preferred treatment has previously been associated with lower dropout rates and better clinical outcomes, but this scenario has not been investigated specifically for psychosocial interventions for patients with a mental health diagnosis.
Objective: To assess the association of patient treatment preference with dropout and clinical outcomes in adult psychosocial mental health interventions via a systematic review and meta-analysis.
Data Sources: The Cochrane Library, Embase, PubMed, PsychINFO, Scopus, Web of Science, Nice HDAS (Healthcare Databases Advanced Search), Google Scholar, BASE (Bielefeld Academic Search Engine), Semantic Scholar, and OpenGrey were searched from inception to July 20, 2018, and updated on June 10, 2019.
Study Selection: Studies were eligible if they (1) were a randomized clinical trial; (2) involved participants older than 18 years; (3) involved participants with mental health diagnoses; (4) reported data from a group of participants who received their preferred treatment and a group who received their nonpreferred treatment or who were not given a choice; and (5) offered at least 1 psychosocial intervention.
Data Extraction and Synthesis: Two researchers extracted study data for attendance, dropout, and clinical outcomes independently. Both assessed the risk of bias according to the Cochrane tool. Data were pooled using random-effects meta-analyses.
Main Outcomes and Measures: The following 7 outcomes were examined: attendance, dropout, therapeutic alliance, depression and anxiety outcomes, global outcomes, treatment satisfaction, and remission.
Results: A total of 7341 articles were identified, with 34 eligible for inclusion. Twenty-nine articles were included in the meta-analyses comprising 5294 participants. Receiving a preferred psychosocial mental health treatment had a medium positive association with dropout rates (relative risk, 0.62; 0.48-0.80; P < .001; I2 = 44.6%) and therapeutic alliance (Cohen d = 0.48; 0.15-0.82; P = .01; I2 = 20.4%). There was no evidence of a significant association with other outcomes.
Conclusions and Relevance: This is the first review, to our knowledge, examining the association of receiving a preferred psychosocial mental health treatment with both engagement and outcomes for patients with a mental health diagnosis. Patients with mental health diagnoses who received their preferred treatment demonstrated a lower dropout rate from treatment and higher therapeutic alliance scores. These findings underline the need to accommodate patient preference in mental health services to maximize treatment uptake and reduce financial costs of premature dropout and disengagement.

PMID: 31799994 [PubMed - as supplied by publisher]

The Alliance of Genome Resources: Building a Modern Data Ecosystem for Model Organism Databases.

Genetics. 2019 Dec;213(4):1189-1196

Authors: Alliance of Genome Resources Consortium

Abstract
Model organisms are essential experimental platforms for discovering gene functions, defining protein and genetic networks, uncovering functional consequences of human genome variation, and for modeling human disease. For decades, researchers who use model organisms have relied on Model Organism Databases (MODs) and the Gene Ontology Consortium (GOC) for expertly curated annotations, and for access to integrated genomic and biological information obtained from the scientific literature and public data archives. Through the development and enforcement of data and semantic standards, these genome resources provide rapid access to the collected knowledge of model organisms in human readable and computation-ready formats that would otherwise require countless hours for individual researchers to assemble on their own. Since their inception, the MODs for the predominant biomedical model organisms [Mus sp (laboratory mouse), Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Danio rerio, and Rattus norvegicus] along with the GOC have operated as a network of independent, highly collaborative genome resources. In 2016, these six MODs and the GOC joined forces as the Alliance of Genome Resources (the Alliance). By implementing shared programmatic access methods and data-specific web pages with a unified "look and feel," the Alliance is tackling barriers that have limited the ability of researchers to easily compare common data types and annotations across model organisms. To adapt to the rapidly changing landscape for evaluating and funding core data resources, the Alliance is building a modern, extensible, and operationally efficient "knowledge commons" for model organisms using shared, modular infrastructure.

PMID: 31796553 [PubMed - in process]

UMLS to DBPedia link discovery through circular resolution.

J Am Med Inform Assoc. 2018 07 01;25(7):819-826

Authors: Cuzzola J, Bagheri E, Jovanovic J

Abstract
Objective: The goal of this work is to map Unified Medical Language System (UMLS) concepts to DBpedia resources using widely accepted ontology relations from the Simple Knowledge Organization System (skos:exactMatch, skos:closeMatch) and from the Resource Description Framework Schema (rdfs:seeAlso), as a result of which a complete mapping from UMLS (UMLS 2016AA) to DBpedia (DBpedia 2015-10) is made publicly available that includes 221 690 skos:exactMatch, 26 276 skos:closeMatch, and 6 784 322 rdfs:seeAlso mappings.
Methods: We propose a method called circular resolution that utilizes a combination of semantic annotators to map UMLS concepts to DBpedia resources. A set of annotators annotate definitions of UMLS concepts returning DBpedia resources while another set performs annotation on DBpedia resource abstracts returning UMLS concepts. Our pipeline aligns these 2 sets of annotations to determine appropriate mappings from UMLS to DBpedia.
Results: We evaluate our proposed method using structured data from the Wikidata knowledge base as the ground truth, which consists of 4899 already existing UMLS to DBpedia mappings. Our results show an 83% recall with 77% precision-at-one (P@1) in mapping UMLS concepts to DBpedia resources on this testing set.
Conclusions: The proposed circular resolution method is a simple yet effective technique for linking UMLS concepts to DBpedia resources. Experiments using Wikidata-based ground truth reveal a high mapping accuracy. In addition to the complete UMLS mapping downloadable in n-triple format, we provide an online browser and a RESTful service to explore the mappings.

PMID: 29648604 [PubMed - indexed for MEDLINE]

Exploring website gist through rapid serial visual presentation.

Cogn Res Princ Implic. 2019 Nov 20;4(1):44

Authors: Owens JW, Chaparro BS, Palmer EM

Abstract
BACKGROUND: Users can make judgments about web pages in a glance. Little research has explored what semantic information can be extracted from a web page within a single fixation or what mental representations users have of web pages, but the scene perception literature provides a framework for understanding how viewers can extract and represent diverse semantic information from scenes in a glance. The purpose of this research was (1) to explore whether semantic information about a web page could be extracted within a single fixation and (2) to explore the effects of size and resolution on extracting this information. Using a rapid serial visual presentation (RSVP) paradigm, Experiment 1 explored whether certain semantic categories of websites (i.e., news, search, shopping, and social networks/blogs) could be detected within a RSVP stream of web page stimuli. Natural scenes, which have been shown to be detectable within a single fixation in the literature, served as a baseline for comparison. Experiment 2 examined the effects of stimulus size and resolution on observers' ability to detect the presence of website categories using similar methods.
RESULTS: Findings from this research demonstrate that users have conceptual models of websites that allow detection of web pages from a fixation's worth of stimulus exposure, when provided additional time for processing. For website categories other than search, detection performance decreased significantly when web elements were no longer discernible due to decreases in size and/or resolution. The implications of this research are that website conceptual models rely more on page elements and less on the spatial relationship between these elements.
CONCLUSIONS: Participants can detect websites accurately when they were displayed for less than a fixation and when the participants were allowed additional processing time. Subjective comments and stimulus onset asynchrony data suggested that participants likely relied on local features for the detection of website targets for several website categories. This notion was supported when the size and/or resolution of stimuli were decreased to the extent that web elements were indistinguishable. This demonstrates that schemas or conceptualizations of websites provided information sufficient to detect websites from approximately 140 ms of stimulus exposure.

PMID: 31748970 [PubMed]

The ethnopharmacological literature: An analysis of the scientific landscape.

J Ethnopharmacol. 2019 Nov 18;:112414

Authors: Kan Yeung AW, Heinrich M, Kijjoa A, Tzvetkov NT, Atanasov AG

Abstract
ETHNOPHARMACOLOGICAL RELEVANCE: The research into bioactive natural products originating from medicinal plants, fungi and other organisms has a long history, accumulating abundant and diverse publications. However no quantitative literature analysis has been conducted.
AIM OF THE STUDY: Here we analyze the bibliometric data of ethnopharmacology literature and relate the semantic content to the publication and citation data so that the major research themes, contributors, and journals of different time periods could be identified and evaluated.
MATERIALS AND METHODS: Web of Science (WoS) was searched to identify relevant publications. The Analyze function of WoS and bibliometric software (VOSviewer) were utilized to perform the analyses.
RESULTS: Until the end of November 2018, 59,576 publications -linked to 'ethnopharmacology' indexed by WoS, published since 1958 in more than 5,600 journals, and contributed by over 20,600 institutions located in more than 200 countries/regions, were identified. The papers were published under four dominating WoS categories, namely pharmacology/pharmacy (34.4%), plant sciences (28.6%), medicinal chemistry (25.3%), and integrative complementary medicine (20.6%). India (14.6%) and China (13.2%) were dominating the publication space. The United States and Brazil also had more than 8.0% contribution each. The rest of the top ten countries/regions were mainly from Asia. There were around ten-fold more original articles (84.6%) than reviews (8.4%).
CONCLUSIONS: Ethnopharmacological research has a consistent focus on food and plant sciences, (bio)chemistry, complementary medicine and pharmacology, with a more limited scientific acceptance in the socio-cultural sciences. Dynamic global contributions have been shifting from developed countries to economically and scientifically emerging countries in Asia, South America and the Middle East. Research on recording medicinal plant species used by traditional medicine continues, but the evaluation of specific properties or treatment effects of extracts and compounds has increased enormously. Moreover increasing attention is paid to some widely distributed natural products, such as curcumin, quercetin, and rutin.

PMID: 31751650 [PubMed - as supplied by publisher]

Cross-lingual Semantic Annotation of Biomedical Literature: Experiments in Spanish and English.

Bioinformatics. 2019 Nov 15;:

Authors: Perez N, Accuosto P, Bravo À, Cuadros M, Martínez-García E, Saggion H, Rigau G

Abstract
MOTIVATION: Biomedical literature is one of the most relevant sources of information for knowledge mining in the field of Bioinformatics. In spite of English being the most widely addressed language in the field, in recent years there has been a growing interest from the natural language processing community in dealing with languages other than English. However, the availability of language resources and tools for appropriate treatment of non-English texts is lacking behind. Our research is concerned with the semantic annotation of biomedical texts in the Spanish language, which can be considered an under-resourced language where biomedical text processing is concerned.
RESULTS: We have carried out experiments to assess the effectiveness of several methods for the automatic annotation of biomedical texts in Spanish. One approach is based on the linguistic analysis of Spanish texts and their annotation using an information retrieval and concept disambiguation approach. A second method takes advantage of a Spanish-English machine translation process to annotate English documents and transfer annotations back to Spanish. A third method takes advantage of the combination of both procedures. Our evaluation shows that a combined system has competitive advantages over the two individual procedures.
AVAILABILITY: UMLSmapper (https://snlt.vicomtech.org/umlsmapper) and the annotation transfer tool (http://scientmin.taln.upf.edu/anntransfer) are freely available for research purposes as web services and/or demos.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID: 31730202 [PubMed - as supplied by publisher]

Exploring semantic deep learning for building reliable and reusable one health knowledge from PubMed systematic reviews and veterinary clinical notes.

J Biomed Semantics. 2019 Nov 12;10(Suppl 1):22

Authors: Arguello-Casteleiro M, Stevens R, Des-Diz J, Wroe C, Fernandez-Prieto MJ, Maroto N, Maseda-Fernandez D, Demetriou G, Peters S, Noble PM, Jones PH, Dukes-McEwan J, Radford AD, Keane J, Nenadic G

Abstract
BACKGROUND: Deep Learning opens up opportunities for routinely scanning large bodies of biomedical literature and clinical narratives to represent the meaning of biomedical and clinical terms. However, the validation and integration of this knowledge on a scale requires cross checking with ground truths (i.e. evidence-based resources) that are unavailable in an actionable or computable form. In this paper we explore how to turn information about diagnoses, prognoses, therapies and other clinical concepts into computable knowledge using free-text data about human and animal health. We used a Semantic Deep Learning approach that combines the Semantic Web technologies and Deep Learning to acquire and validate knowledge about 11 well-known medical conditions mined from two sets of unstructured free-text data: 300 K PubMed Systematic Review articles (the PMSB dataset) and 2.5 M veterinary clinical notes (the VetCN dataset). For each target condition we obtained 20 related clinical concepts using two deep learning methods applied separately on the two datasets, resulting in 880 term pairs (target term, candidate term). Each concept, represented by an n-gram, is mapped to UMLS using MetaMap; we also developed a bespoke method for mapping short forms (e.g. abbreviations and acronyms). Existing ontologies were used to formally represent associations. We also create ontological modules and illustrate how the extracted knowledge can be queried. The evaluation was performed using the content within BMJ Best Practice.
RESULTS: MetaMap achieves an F measure of 88% (precision 85%, recall 91%) when applied directly to the total of 613 unique candidate terms for the 880 term pairs. When the processing of short forms is included, MetaMap achieves an F measure of 94% (precision 92%, recall 96%). Validation of the term pairs with BMJ Best Practice yields precision between 98 and 99%.
CONCLUSIONS: The Semantic Deep Learning approach can transform neural embeddings built from unstructured free-text data into reliable and reusable One Health knowledge using ontologies and content from BMJ Best Practice.

PMID: 31711540 [PubMed - in process]

Development of a Free Online Interactive Naming Therapy for Bilingual Aphasia.

Am J Speech Lang Pathol. 2019 Nov 05;:1-10

Authors: Sandberg C, Gray T, Kiran S

Abstract
Purpose The purpose of this ongoing project was to provide speech-language pathologists who serve culturally and linguistically diverse populations with a freely available online tool for naming therapy in a variety of languages. The purpose of this clinical focus article was to report on this resource in an effort to make known its existence, its instructions for use, and the evidence-based practices from which it was developed. Method The website, bilingualnamingtherapy.com, was created by the research team in collaboration with a web programmer using Amazon Web Services. The treatment protocol for the website was adapted from an evidence-based naming intervention in which clients select and verify appropriate semantic features for the target words. This protocol comes from the work of Kiran and colleagues (Edmonds & Kiran, 2006; Kiran & Iakupova, 2011; Kiran & Lo, 2013; Kiran & Roberts, 2010; Kiran, Sandberg, Gray, Ascenso, & Kester, 2013; Krishnan, Tiwari, Kiran, & Chengappa, 2014), who showed positive benefits of this therapy within and across languages in bilingual persons with aphasia. The stimuli for the online therapy were developed in a variety of languages. First, words and semantic features were translated from English to 10 different languages. Next, surveys were created using Qualtrics software and posted on Amazon Mechanical Turk to verify picture labels and semantic features for each word in each language. The results of these surveys guided the stimuli used for each language on the website. An interactive website was developed to allow clinicians to select a set of words and progress through a series of steps. A step-by-step tutorial on how to use this website is also included in this article. Conclusions The interactive online naming therapy described in this article is currently available in English and Spanish, with Chinese under construction. Several more languages are in various stages of preparation for use on the website, and suggestions for additional languages are being actively sought. Bilingualnamingtherapy.com promises to be a useful tool for speech-language pathologists who work with culturally and linguistically diverse clients. This website provides naming therapy materials, adapted from an evidence-based protocol, in a variety of languages, that have been developed based on feedback from speakers of each language to maximize cultural and linguistic appropriateness.

PMID: 31689369 [PubMed - as supplied by publisher]