Search Results for "text extraction"

TIES (Text Information Extraction System) is a clinical text search engine that uses Natural Language Processing techniques to extract medical concepts from free text clinical reports. It provides secure de-identified access to this information and has in built collaboration tools and honest broker functionality. It is licensed for academic use under the BSD license.

Biomedical Text Mining (BioTM) is providing valuable approaches to the automated curation of scientific literature.

Turku Event Extraction System (TEES) is a free and open source natural language processing system developed for the extraction of events and relations from biomedical text. It is written mostly in Python, and should work in generic Unix/Linux environments. Currently, the TEES source code repository still remains on GitHub at http://jbjorne.github.com/TEES/ where there is also a wiki with more information.

...Either the X & Y intensities for creating cluster plots or Log R Ratio and B Allele Frequencies for CNV detection. Extracting the data for individual SNP/CNV markers or individual samples was slow grep/awk'ing the text files exported from the genotyping run (e.g. Illumina final report files). bint converts the text representation of the intensity float data to into a IEEE754 indexed binary file for rapid extraction of subsets of the data. In theory bint could be used for any large tables of float data.

This is a Java-based project for complex event extraction from text and co-reference resolution. Currently the code can read BioNLP shared task format (http://2011.bionlp-st.org/) and i2b2 Natural Language Processing for Clinical Data shared task format (https://www.i2b2.org/NLP/DataSets/Main.php). Event extraction includes finding events and the parameters for an event in a text.

Moara is a biological text mining tool and consists of a Java library and some auxiliary MySQL databases for gene/protein training and extraction of mentions and its further normalization and disambiguation.

OpenDMAP (Open Source Direct Memory Access Parser) is a natural language processing (text mining) application: a semantic parser for information extraction.

MutationFinder is a biomedical natural language processing (NLP) system for extracting mentions of point mutations from free text. MutationFinder achieves high performance (99% precision, 81% recall on blind test data) as an information extraction system

UIMA-compliant text analytics using a rule language in which to express context-sensitive constraints on syntactic and semantic text elements.

BioEval, a web-based evaluation platform for one or multiple biomedical text extraction systems and the collaborative creation of gold standards. Handles evaluation of extraction of one to many related entities, plus supporting evidence and normalization

GraphSpider is a pattern matcher which searches parsed text in phrase-structure tree or dependency graph format for syntactic structures matching a set of patterns in MPL, a regexp-like pattern language. Applications: information extraction, text mining.

PubMed Central browser. Source code: http://github.com/dualword/dualword-pmc/