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      SciReader enables reading of medical content with instantaneous definitions

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          Abstract

          Background

          A major problem patients encounter when reading about health related issues is document interpretation, which limits reading comprehension and therefore negatively impacts health care. Currently, searching for medical definitions from an external source is time consuming, distracting, and negatively impacts reading comprehension and memory of the material.

          Methods

          SciReader was built as a Java application with a Flex-based front-end client. The dictionary used by SciReader was built by consolidating data from several sources and generating new definitions with a standardized syntax. The application was evaluated by measuring the percentage of words defined in different documents. A survey was used to test the perceived effect of SciReader on reading time and comprehension.

          Results

          We present SciReader, a web-application that simplifies document interpretation by allowing users to instantaneously view medical, English, and scientific definitions as they read any document. This tool reveals the definitions of any selected word in a small frame at the top of the application. SciReader relies on a dictionary of ~750,000 unique Biomedical and English word definitions. Evaluation of the application shows that it maps ~98% of words in several different types of documents and that most users tested in a survey indicate that the application decreases reading time and increases comprehension.

          Conclusions

          SciReader is a web application useful for reading medical and scientific documents. The program makes jargon-laden content more accessible to patients, educators, health care professionals, and the general public.

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          Most cited references16

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Medical Subject Headings (MeSH).

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              Is Open Access

              Database resources of the National Center for Biotechnology Information

              In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, Reference Sequence, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Entrez Probe, GENSAT, Online Mendelian Inheritance in Man, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Peptidome, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.
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                Author and article information

                Journal
                BMC Med Inform Decis Mak
                BMC Medical Informatics and Decision Making
                BioMed Central
                1472-6947
                2011
                25 January 2011
                : 11
                : 4
                Affiliations
                [1 ]School of Life Sciences, University of Nevada, Las Vegas, 4505 Maryland Pkwy., Las Vegas, NV 89154-4004 USA
                [2 ]Department of Molecular, Microbial, and Structural Biology, University of Connecticut Heath Center, 263 Farmington Ave., Farmington, CT 06030-3305 USA
                Article
                1472-6947-11-4
                10.1186/1472-6947-11-4
                3038137
                21266060
                691d22cf-1058-470d-b5c9-8f77bcbf5fac
                Copyright ©2011 Gradie et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 August 2010
                : 25 January 2011
                Categories
                Software

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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