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Snofyre

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Snofyre is an open source, service oriented API for creating SNOMED CT enabled applications in Java. It provides a number of SNOMED CT related services out of the box. These services can be used:

  • as a starter for understanding how to add SNOMED CT functionality to an application.
  • to rapidly prototype a SNOMED CT enabled application.

Snofyre API aims to

  • reduce the 'ramp up' time needed to understand
  • and embed SNOMED CT functionality in an application.
Homepage: 
http://code.google.com/p/snofyre/

Perl HL7 Toolkit

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This project provides a simple but flexible Perl Toolkit for using the HL7 protocol. The toolkit consists of a Perl API, an implementation of a pluggable forking HL7 server, and an HL7 message queue daemon for developing HL7 capable applications in Perl.

Homepage: 
http://hl7toolkit.sourceforge.net/

PyEEG

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A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectral analysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.

Homepage: 
http://code.google.com/p/pyeeg/

Ruby HL7

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Your rating: None Average: 2.4 (5 votes)

Ruby HL7 is a simple library for parsing and generating HL7 2.x messages. 3.x support is planned in the future.

Homepage: 
http://rubyforge.org/projects/ruby-hl7

WEKA

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Your rating: None Average: 2.7 (3 votes)

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

Homepage: 
http://www.cs.waikato.ac.nz/ml/weka/

Dataserver

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"DataServer is an open source XML gateway, specially tailored for the medical domain. DataServer is middleware, situated between clients and traditional Health Information Systems (HIS), Radiology Information Systems (RIS) and Picture Archive and Communication Systems (PACS). It supports relational (SQL), SOAP, and HTTP data sources out of the box, but is highly extensible for custom types."

Homepage: 
http://www.mii.ucla.edu/dataserver/

Brainstorm

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Brainstorm is a collaborative open-source Matlab application dedicated to magnetoencephalography (MEG) and electroencephalography(EEG) data visualization, processing and cortical source estimation.
The intention is to make a comprehensive set of tools available to the scientific community involved in MEG/EEG experimental research.
For physicians and researchers, the interest of this software package resides in its rich and intuitive graphic interface, which does not require any programming knowledge.

Homepage: 
http://neuroimage.usc.edu/brainstorm

BioSig

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BioSig is an open source software library for biomedical signal processing, featuring for example the analysis of biosignals such as the electroencephalogram (EEG), electrocorticogram (ECoG), electrocardiogram (ECG), electrooculogram (EOG), electromyogram (EMG), respiration, and so on. Major application areas are: Neuroinformatics, brain-computer interfaces, neurophysiology, psychology, cardiovascular systems and sleep research. The aim of the BioSig project is to foster research in biomedical signal processing by providing open source software tools for many different applications.

Homepage: 
http://biosig.sourceforge.net/

MediPy

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Your rating: None Average: 3.2 (5 votes)

MediPy is a cross-platform software (Windows, Linux, Mac OS), dedicated to the visualization and processing aspects of medical imaging. It is targeted at both physicians and researchers, being both user-friendly and easy to extend. Physicians will benefit from the pre-programmed tasks (e.g. segmentation, registration, detection of lesions) and the possibility to record new tasks, tailoring the software to each user. The use of standard file formats (Analyze/Nifti, Dicom) allows to load image from many sources, as well as integrate to a PACS.

Homepage: 
https://code.google.com/p/medipy/

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