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OpenSourcePACS

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Your rating: None Average: 3.9 (22 votes)

OpenSourcePACS is a free, open source image referral, archiving, routing and viewing system. It adds functionality beyond conventional PACS by integrating wet read functions, implemented through DICOM Presentation State and Structured Reporting standards.

In its first release, OpenSourcePACS delivers a complete wet read system, enabling an imaging clinic or hospital to offer its services over the web to physicians within or outside the institution. In future releases, we hope to incorporate more RIS (dictation, transcription, and reporting) functionality.

GT.M

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Your rating: None Average: 3.3 (3 votes)

GT.M is a FOSS (AGPL v3) implementation of M (also known as MUMPS), a combination of a procedural programming language well integrated with a hierarchical key-value database engine. M is widely used in enterprise scale healthcare applications and application suites, such as the VistA implementations. GT.M scales up to very large databases (the largest production sites have aggregate databases to several TB) and thousands of concurrent users.

GNU Gluco Control

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Your rating: None Average: 3.8 (4 votes)

GNU Gluco Control (ggc) helps you to manage your diabetes. It helps managing user's daily data, food data. Has graphs, statistics, printing, meters support and pump support (work in progress).

CASE

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The main goal of the Computer Assisted Search for Epidemics (CASE) project is to develop a reliable system that generates warnings when the number of reported cases of a particular infectious disease reaches a level that indicates an unusual or unexpected rate. The system is currently in use at the Swedish Institute for Infectious Disease Control (SMI). It performs daily surveillance using data obtained from the database to which all notifiable diseases are reported in Sweden.

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.

RT_Image

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Your rating: None Average: 4 (4 votes)

RT_Image is an application developed in the Department of Radiation Oncology and MIPS at Stanford University. Coded in the Interactive Data Language (IDL, ITT Visual Information Solutions), RT_Image was originally designed in 2003 to generate radiotherapy target volumes from positron emission tomography (PET) datasets. It has since evolved to embody a variety of tools for visualizing, quantitating, and segmenting three-dimensional images.

JCAM Engine

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Your rating: None Average: 3 (2 votes)

XML Validation Framework and Canonical XML dictionary-based exchange assembly - OASIS CAM

The OASIS CAM toolkit provides a suite of tools for XML Validation and XML Exchange design and assembly from canonical XML dictionary components.

Included in the toolkit is an XML Editor/Validation/Schema Designer along with the CAMV runtime XML validation engine.

The project implements the OASIS CAM standard & NIEM IEPD approach. The visual editor allows design of exchange structures using XML components dictionaries.

PyEEG

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Your rating: None Average: 2 (4 votes)

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.

C# ECG Toolkit

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Your rating: None Average: 2.5 (17 votes)

C# ECG Toolkit is an open source software toolkit to convert, view and print electrocardiograms. The toolkit is developed using C# .NET 1.1 & 2.0. Support for ECG formats: SCP-ECG, DICOM and HL7 aECG.

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.

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