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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.

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.

rxncon

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The complexity of cellular networks is an outstanding challenge for documentation, visualisation and mathematical modelling. In this project, we develop a new way to describe these networks that minimises the combinatorial complexity and allows an automatic visualisation and export of mathematical (ODE/rulebased) models.

Features:

  • Automatic visualiztion with Cytoscape.
  • Automatic generation of rule based models for BioNetGen.
  • Storage of biological facts that can be used for modelling.

Laika

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Laika analyzes and reports on the interoperability capabilities of EHR systems. This includes the testing for certification of EHR software products and networks.

To support EHR data interoperability testing, Laika is designed to verify the input and output of EHR data against the standards and criteria identified by the Certification Commission for Health Information Technology (CCHIT). Laika is used by the Certification Commission to perform part of the interoperability certification inspection of EHRs.

GNU Octave

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GNU Octave is a high-level language, primarily intended for numerical computations. It provides a convenient command line interface for solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with Matlab. It may also be used as a batch-oriented language.

PyMVPA

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Your rating: None Average: 3.7 (3 votes)

"PyMVPA is a Python module intended to ease pattern classification analyses of large datasets. In the neuroimaging contexts such analysis techniques are also known as decoding or MVPA analysis. PyMVPA provides high-level abstraction of typical processing steps and a number of implementations of some popular algorithms. While it is not limited to the neuroimaging domain, it is eminently suited for such datasets. PyMVPA is truly free software (in every respect) and additionally requires nothing but free-software to run."

Gwyddion

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Gwyddion is a modular program for SPM (scanning probe microscopy) data visualization and analysis. Primarily it is intended for analysis of height fields obtained by scanning probe microscopy techniques (AFM, MFM, STM, SNOM/NSOM), however it can be generally used for any other height field and image analysis, for instance for analysis of profilometry data.

It aims to provide multiplatform modular program for 2D data analysis that could be easily extended by modules and plug-ins.

EGADSS

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Your rating: None Average: 2.1 (11 votes)

EGADSS (Evidence-based Guideline and Decision Support System) is an open source tool that is designed to work in conjunction with primary care Electronic Medical Record (EMR) systems to provide patient specific point of care reminders in order to aid physicians provide high quality care. EGADSS is designed as a stand alone system that would respond to requests from existing Electronic Medical Records such as Wolf, Med Access, and MedOffIS to provide patient specific clinical guidance based on its internal collection of guidelines.

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