924 research outputs found

    Analysis of biomedical and health queries: Lessons learned from TREC and CLEF evaluation benchmarks

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    International audienceBACKGROUND:Inherited ichthyoses represent a group of rare skin disorders characterized by scaling, hyperkeratosis and inconstant erythema, involving most of the tegument. Epidemiology remains poorly described. This study aims to evaluate the prevalence of inherited ichthyosis (excluding very mild forms) and its different clinical forms in France.METHODS:Capture - recapture method was used for this study. According to statistical requirements, 3 different lists (reference/competence centres, French association of patients with ichthyosis and internet network) were used to record such patients. The study was conducted in 5 areas during a closed period.RESULTS:The prevalence was estimated at 13.3 per million people (/M) (CI95\%, [10.9 - 17.6]). With regard to autosomal recessive congenital ichthyosis, the prevalence was estimated at 7/M (CI 95\% [5.7 - 9.2]), with a prevalence of lamellar ichthyosis and congenital ichthyosiform erythroderma of 4.5/M (CI 95\% [3.7 - 5.9]) and 1.9/M (CI 95\% [1.6 - 2.6]), respectively. Prevalence of keratinopathic forms was estimated at 1.1/M (CI 95\% [0.9 - 1.5]). Prevalence of syndromic forms (all clinical forms together) was estimated at 1.9/M (CI 95\% [1.6 - 2.6]).CONCLUSIONS:Our results constitute a crucial basis to properly size the necessary health measures that are required to improve patient care and design further clinical studies

    Order of Magnitude Reductions in the Size of Enterprise Search Result Sets Through the Use of Subject Indexes

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    Keyword search has failed to adequately meet the needs of enterprise users. This is largely due to the indeterminate nature of languages. We argue a different approach needs to be taken, and draw on the success of previous library indexing concepts to propose a solution. We test our solution by performing search queries on a large research database. By incorporating readily available subject indexes into the search process, we obtain order of magnitude improvements in the performance of search queries. Our performance measure is the ratio of the number of documents returned without using subject indexes to the number of documents returned when subject indexes are used. We explain why the observed tenfold improvement in search performance on our research database can be expected to occur for searches on a wide variety of enterprise document stores

    Still a Lot to Lose: The Role of Controlled Vocabulary in Keyword Searching

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    In their 2005 study, Gross and Taylor found that more than a third of records retrieved by keyword searches would be lost without subject headings. A review of the literature since then shows that numerous studies, in various disciplines, have found that a quarter to a third of records returned in a keyword search would be lost without controlled vocabulary. Other writers, though, have continued to suggest that controlled vocabulary be discontinued. Addressing criticisms of the Gross/Taylor study, this study replicates the search process in the same online catalog, but after the addition of automated enriched metadata such as tables of contents and summaries. The proportion of results that would be lost remains high

    Improving search over Electronic Health Records using UMLS-based query expansion through random walks

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    ObjectiveMost of the information in Electronic Health Records (EHRs) is represented in free textual form. Practitioners searching EHRs need to phrase their queries carefully, as the record might use synonyms or other related words. In this paper we show that an automatic query expansion method based on the Unified Medicine Language System (UMLS) Metathesaurus improves the results of a robust baseline when searching EHRs.Materials and methodsThe method uses a graph representation of the lexical units, concepts and relations in the UMLS Metathesaurus. It is based on random walks over the graph, which start on the query terms. Random walks are a well-studied discipline in both Web and Knowledge Base datasets.ResultsOur experiments over the TREC Medical Record track show improvements in both the 2011 and 2012 datasets over a strong baseline.DiscussionOur analysis shows that the success of our method is due to the automatic expansion of the query with extra terms, even when they are not directly related in the UMLS Metathesaurus. The terms added in the expansion go beyond simple synonyms, and also add other kinds of topically related terms.ConclusionsExpansion of queries using related terms in the UMLS Metathesaurus beyond synonymy is an effective way to overcome the gap between query and document vocabularies when searching for patient cohorts

    Holes in the Outline : Subject-dependent Abstract Quality and its Implications for Scientific Literature Search

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    Scientific literature search engines typically index abstracts instead of the full-text of publications. The expectation is that the abstract provides a comprehensive summary of the article, enumerating key points for the reader to assess whether their information needs could be satisfied by reading the full-text. Furthermore, from a practical standpoint, obtaining the full-text is more complicated due to licensing issues, in the case of commercial publishers, and resource limitations of public repositories and pre-print servers. In this article, we use topic modelling to represent content in abstracts and full-text articles. Using Computer Science as a case study, we demonstrate that how well the abstract summarises the full-text is subfield-dependent. Indeed, we show that abstract representativeness has a direct impact on retrieval performance, with poorer abstracts leading to degraded performance. Finally, we present evidence that how well an abstract represents the full-text of an article is not random, but is a consequence of style and writing conventions in different subdisciplines and can be used to infer an "evolutionary" tree of subfields within Computer Science.Peer reviewe

    Exploring the Referral and Usage of Science Fiction in HCI Literature

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    Research on science fiction (sci-fi) in scientific publications has indicated the usage of sci-fi stories, movies or shows to inspire novel Human-Computer Interaction (HCI) research. Yet no studies have analysed sci-fi in a top-ranked computer science conference at present. For that reason, we examine the CHI main track for the presence and nature of sci-fi referrals in relationship to HCI research. We search for six sci-fi terms in a dataset of 5812 CHI main proceedings and code the context of 175 sci-fi referrals in 83 papers indexed in the CHI main track. In our results, we categorize these papers into five contemporary HCI research themes wherein sci-fi and HCI interconnect: 1) Theoretical Design Research; 2) New Interactions; 3) Human-Body Modification or Extension; 4) Human-Robot Interaction and Artificial Intelligence; and 5) Visions of Computing and HCI. In conclusion, we discuss results and implications located in the promising arena of sci-fi and HCI research.Comment: v1: 20 pages, 4 figures, 3 tables, HCI International 2018 accepted submission v2: 20 pages, 4 figures, 3 tables, added link/doi for Springer proceedin

    Linked Opinions: Describing Sentiments on the Structured Web of Data

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    In the paper we report on the results of our experiments on the construction of the opinion ontology. Our aim is to show the benefits of publishing in the open, on the Web, the results of the opinion mining process in a structured form. On the road to achieving this, we attempt to answer the research question to what extent opinion information can be formalized in a unified way. Furthermore, as part of the evaluation, we experiment with the usage of Semantic Web technologies and show particular use cases that support our claims

    A guide to writing systematic reviews of rare disease treatments to generate FAIR-compliant datasets: Building a Treatabolome

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    Background: Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their rarity translates into a delayed diagnosis, with 25% of patients waiting 5 to 30 years for one. It is essential to raise awareness of patients and clinicians of existing gene and variant-specific therapeutics at the time of diagnosis to avoid that treatment delays add up to the diagnostic odyssey of rare diseases' patients and their families. Aims: This paper aims to provide guidance and give detailed instructions on how to write homogeneous systematic reviews of rare diseases' treatments in a manner that allows the capture of the results in a computer-accessible form. The published results need to comply with the FAIR guiding principles for scientific data management and stewardship to facilitate the extraction of datasets that are easily transposable into machine-actionable information. The ultimate purpose is the creation of a database of rare disease treatments ("Treatabolome") at gene and variant levels as part of the H2020 research project Solve-RD. Results: Each systematic review follows a written protocol to address one or more rare diseases in which the authors are experts. The bibliographic search strategy requires detailed documentation to allow its replication. Data capture forms should be built to facilitate the filling of a data capture spreadsheet and to record the application of the inclusion and exclusion criteria to each search result. A PRISMA flowchart is required to provide an overview of the processes of search and selection of papers. A separate table condenses the data collected during the Systematic Review, appraised according to their level of evidence. Conclusions: This paper provides a template that includes the instructions for writing FAIR-compliant systematic reviews of rare diseases' treatments that enables the assembly of a Treatabolome database that complement existing diagnostic and management support tools with treatment awareness data
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