Search Results for "bio-bwa"

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. For commercial use please contact Nexi at http://nexihub.com *** NOTICE: this software and forum are no longer...

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.

A minimalist approach to share text documents and data annotations. Allows a large number of different annotations to be represented. Project files contain: - simple code to hold/read/write data and perform sample processing. - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are...

BANNER is a named entity recognition system intended primarily for biomedical text. It uses conditional random fields as the primary recognition engine and includes a wide survey of the best techniques described in recent literature.

Drug name recognition and normalisation/grounding to DrugBank ids and standard names. Package provides 2 taggers: 1. DrugTagger - CRF-based with DrugBank presence feature (see feature set for details). 2. DrugnameGazetteer - gazetteer/dictionary-based. Dictionary created from DrugBank.ca database. Both taggers include grounding/normalisation to DrugBank ids and standard names. Feature set: Word, Word-1, Word+1, Word-1_Word, Word_Word+1, DrugBankPresence, POS DrugBankPresence...

This application was developed by the NIHR Biomedical Research Centre at the Institute of Psychiatry and South London and Maudsley NHS Foundation Trust, in collaboration with the University of Sheffield. Its purpose is to identify the smoking status of a individual, based on text evidence in clinical notes. Currently, it classifies patients as 'current', 'past' or 'never'. It runs on the GATE infrastructure, available at http://gate.ac.uk/. Please contact richard.g.jackson@slam.nhs.uk for...

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. The method is based on SVM but other ML algorithms can be adopted. The method details are explained in the...

The Parenthesis Classifier takes the contents of a set of parentheses and classifies it into one of several categories. It includes a parenthesized-data extractor and the classifier.

Give names to the colors your eyes see, watch the computer learn and suggest names for new randomic colors. It gives the RGB components of each colors and list the memory so on, saving it into a text file with your name.

ANT is a lightweight implementation in C of a kind of artificial neural net called Multilayer Perceptron, which uses the backpropagation algorithm as learning method. The package includes an introductory example to start using artificial neural nets.

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

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