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Andrea Owen

Andrea Owen's Public Library

ColorBrewer - Selecting Good Color Schemes

Presentation friendly colour scheme options - look for the lcd projector image, if its crossed out then the scheme isn't a good choice for your presentation. I like, for an 8 class colour set to click on 'qualitative' and use 'set 1' which starts with red. It says this set is suitable for lcd projector, laptop and CRT displays.

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colorbrewer presentation

MRC Psycholinguistic Database Machine Usable Dictionary

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

ota.oucs.ox.ac.uk/...1054.xml - Preview

dictionary attributes

11 May 09

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

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.

www.jstor.org/...748099.pdf - Preview

reading process automated cognition

The SPECIALIST NLP Tools

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.

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UMLS NLM indexing tools automated analysis tagging lexicon medical terms

Content and Structure of Clinical Problem Lists: A Corpus Analysis

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.

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automatic tagging UMLS concepts semantic processing medical language

22 Apr 09

Methodspace

supporting researchers with online discussions about research methods and courses

www.methodspace.com - Preview

research methods courses

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