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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."

Voreen

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Your rating: None Average: 3.3 (6 votes)

Voreen is an open source rapid application development framework for the interactive visualization and analysis of multi-modal volumetric data sets. It provides GPU-based volume rendering and data analysis techniques and offers high flexibility when developing new analysis workflows in collaboration with domain experts. The Voreen framework consists of a multi-platform C++ library, which can be easily integrated into existing applications, and a Qt-based stand-alone application.

Zyxware Health Monitoring System

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Your rating: None Average: 4.5 (2 votes)

Zyxware Health Monitoring System is a web based disease monitoring for monitoring diseases like chikungunya, malaria - reported by hospitals in a district, county, state or country. There is a reporting & analysis module and a GIS module which displays the data using google maps.

Ginkgo CADx

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Your rating: None Average: 4 (4 votes)

Ginkgo CADx project started in 2009 with the aim to create an interactive, universal, homogeneous, open-source and cross-platform CADX environment.

Ginkgo is built over a huge amount of advanced technologies providing full abstraction of complex tasks as:

QuickViewHL7

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Your rating: None Average: 4.3 (4 votes)

HL7 file viewer, in tree-view format, with associated segment/field documentation. The latest release now includes editing, at all levels in the tree-view, e.g segment, field or component values. Purpose is for testing and bug-tracing HL7 communications.

Epigrass

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Your rating: None Average: 2.5 (2 votes)

Epigrass is a open-source simulation platform created to study epidemics and their spatial (geographic) dinamics.

Epigrass was developed as a scientific project, by the founders of Metamodellers at the Oswaldo Cruz Foundation. Currently, Metamodellers is the main maintainer of the code, ensuring its continuous improvement while remaining a completely free tool.

MIView

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Your rating: None Average: 2 (5 votes)

MIView is an OpenGL based medical image viewer that contains useful tools such as a DICOM anonymizer and format conversion utility. MIView can read DICOM, Analyze/Nifti, and raster images, and can write Analyze/Nifti and raster images. It can also read and convert DICOM mosaic images. The main goal of MIView is to provide a platform to load any type of medical image and be able to view and manipulate the image. Volume rendering is the main type of advanced visualization that I'm trying to implement.

cancer Biomedical Informatics Grid (caBIG)

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Your rating: None Average: 3 (2 votes)

The National Cancer Institute (NCI) has launched the caBIG initiative to accelerate research discoveries and improve patient outcomes by linking researchers, physicians, and patients throughout the cancer community.

The 'DiagnosisMed' R Package

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Your rating: None Average: 4 (1 vote)

DiagnosisMed is a package to analyze data from diagnostic test accuracy evaluating health conditions. It is being built to be used by health professionals. This package is able to estimate sensitivity and specificity from categorical and continuous test results including some evaluations of indeterminate results, or compare different categorical tests, and estimate reasonble cut-offs of tests and display it in a way commonly used by health professionals. No graphical interface is avalible yet. Partners are most welcome.

WEKA

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Your rating: None Average: 3 (2 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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