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Andrea Owen

Content and Structure of Clinical Problem Lists: A Corpus Analysis - 0 views

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    Clinical Document Collection: A collection of 7673 initial visit notes was obtained from the Columbia University Medical Center Milstein Hospitalist Service. This includes all resident and attending initial visit notes and initial consult notes for inpatient admissions of all types from late 2006 through early 2007. They are not filtered and should therefore be representative of all patients admitted to the Hospitalist Service. All notes from the Service are entered through semi-structured entry templates in a system called eNote11. PMH was entered into a coded field in eNote templates, but as free text within that field. The advantage for this analysis was that these lists were in the doctor's own words without any limits on structure or content imposed by the information system. The notes were stored using the Clinical Document Architecture (CDA) XML schema. This allowed for a simple XSL transformation to filter protected health information (PHI) and convert sections of interest to text. A small Java application was written to perform this XSLT on each document and do basic preprocessing to prepare the text for natural language processing analysis. Data Preparation: The corpus was then parsed with the MedLEE natural language processor12 to obtain the semantic structure and UMLS codes of concepts represented in these notes. MedLEE output was generated as XML and a Java postprocessor was used to validate the XML output. Each note section was divided into a text section with numbered phrase tags around identifiable phrases and a structured element containing references describing the tagged phrases. Reference tags were named with the phrase's semantic type. MedLEE assigned a UMLS code to the phrase whenever it could map the clinical information detected to known UMLS concepts. MedLEE results were then merged into one large XML file to facilitate querying across all documents with XQuery.
Andrea Owen

MRC Psycholinguistic Database Machine Usable Dictionary - 0 views

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    Title * MRC Psycholinguistic Database Machine Usable Dictionary [Electronic resource] : expanded Shorter Oxford English Dictionary entries / Max Coltheart and Michael Wilson Author Coltheart, M. (Max), 1939-; Wilson, Michael John, 1939- Availability Freely available for non-commercial use provided that this header is included in its entirety with any copy distributed. This resource is freely available, you should be able to download it now. Languages English; Editorial Practice * Encoding format: MS Word and UNIX OTA keywords Dictionaries LC keywords Psycholinguistics -- Dictionaries Extent * designation: Text data * size: (16 files : ca. 12.5 megabytes) Creation Date [198?] Source Description MRC Psycholinguistic Database Machine Usable Dictionary : expanded Shorter Oxford English Dictionary entries Coltheart, M. (Max), 1939-; Wilson, Michael John, 1939- s.n. s.l.: s.d [Note: For additional information see: Coltheart, Max.--"MRC Psycholinguistic database" in Quarterly Journal of Experimental Psychology 33A (1981):497-505.--Catalogued on RLIN] Notes * Mode of access: Offline. Application to OTA * Title proper taken from electronic text
anonymous

Retrieval Practice Produces More Learning than Elaborative Studying with Concept Mappin... - 0 views

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    Here, we show that practicing retrieval produces greater gains in meaningful learning than elaborative studying with concept mapping. The advantage of retrieval practice generalized across texts identical to those commonly found in science education. The advantage of retrieval practice was observed with test questions that assessed comprehension and required students to make inferences. The advantage of retrieval practice occurred even when the criterial test involved creating concept maps. Our findings support the theory that retrieval practice enhances learning by retrieval-specific mechanisms rather than by elaborative study processes. Retrieval practice is an effective tool to promote conceptual learning about science.
Andrea Owen

The SPECIALIST NLP Tools - 0 views

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    The SPECIALIST Natural Language Processing (NLP) Tools have been developed by the The Lexical Systems Group of The Lister Hill National Center for Biomedical Communications to investigate the contributions that natural language processing techniques can make to the task of mediating between the language of users and the language of online biomedical information resources. The SPECIALIST NLP Tools facilitate natural language processing by helping application developers with lexical variation and text analysis tasks in the biomedical domain. The NLP Tools are open source resources distributed subject to these terms and conditions.
Andrea Owen

The Interplay between Automatic and Control Processes in Reading Author(s): Jeffrey J. ... - 0 views

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    Reading is characterized by the successful coor- dination of a number of concurrent processing layers (Pressley & Afflerbach, 1995). Many pro- I cessing activities occur automatically for the ex- perienced reader, such as lexical access, anaphor resolution (deciding to whom the author refers), and proposition integration. Others require the allocation of conscious attention, for instance, when elaborating on text meaning or when generating bridging inferences to integrate meanings across paragraphs (Kintsch, 1993). Although reading requires a coordination between auto- matic and attention-demanding (control) processing activ- ities, existent models of reading provide at best only a partial understanding of how the two processing types interact.
Andrea Owen

Medical_Text_Indexer_Processing_Flow.pdf (application/pdf Object) - 0 views

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    Medical Text Indexer (MTI)
anonymous

digitalresearchtools / FrontPage - 0 views

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    This wiki collects information about tools and resources that can help scholars (particularly in the humanities and social sciences) conduct research more efficiently or creatively. Whether you need software to help you manage citations, author a multimedia work, or analyze texts, Digital Research Tools will help you find what you're looking for. We provide a directory of tools organized by research activity, as well as reviews of select tools in which we not only describe the tool's features, but also explore how it might be employed most effectively by researchers.
Andrea Owen

Wordle: Create a word frequency cloud - 0 views

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    This is a brilliant tool, and its not necessary to leave any data in the public domain as the resulting file can be saved to file. Lots of fonts etc.
Andrea Owen

comparing corpora using frequency profiling - 0 views

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    paul rayson and roger garside UCREL Lancaster University
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