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Real-time Outbreak and Disease Surveillance (RODS)

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Your rating: None Average: 2.7 (6 votes)

"Real-time Outbreak and Disease Surveillance (RODS) is open-source public health surveillance software. RODS collects and analyzes disease surveillance data in real time and has been in development since 1999 by the RODS Laboratory. In 2002, the Utah Department of Health used the software for monitoring during the Winter Olympics Games. At present, health departments and other groups in the United States, Canada and Taiwan use the software."

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.

Laika

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Your rating: None Average: 3.5 (4 votes)

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.

PixelMed Java DICOM Toolkit

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Your rating: None Average: 3.6 (15 votes)

PixelMed Java DICOM Toolkit is a stand-alone DICOM toolkit that implements code for reading and creating DICOM data, DICOM network and file support, a database of DICOM objects, support for display of directories, images, reports and spectra, and DICOM object validation.

The toolkit is a completely new implementation, which does not depend on any other DICOM tools, commercial or free. It does make use of other freely available pure Java tools for compression and XML and database support.

Project HealthDesign Common Platform

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Your rating: None Average: 2.3 (3 votes)

The Project HealthDesign Common Platform is a set of software components that provide common, shared functions to a variety of personal health applications (PHAs). The goal of “centralizing” these functions is to reduce personal health application implementation time and increase interoperability among the PHAs. The common platform components are currently implemented as web services that PHAs may access via standard web interfaces. Services exist for storing observations and medications, as well as for providing authentication, registry, and access-control functions.

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.

MITK 3M3

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Your rating: None Average: 4 (3 votes)

MITK 3M3 is a free and user-friendly application which ensures effective and efficient work, analysis, and visualization of radiological image data.

MITK 3M3 gives you access to the latest algorithms and methods from research. The cooperation between the German Cancer Research Center (DKFZ) and mint medical allows for a rapid transfer of leading-edge research topics, including diffusion imaging and automated segmentation techniques. MITK 3M3 will be constantly extended with the addition of new software modules to bring the latest research work to your computer.

Xebra

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Your rating: None Average: 3.1 (15 votes)

Xebra is an open source, cross-platform, thin client and server for web-based distribution and clinical review of medical imaging results. Xebra is based on the latest open industry standards including JPEG2000, WADO and IHE XDS-I.

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.

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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