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GNUmed

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The GNUmed project builds free, liberated open source Electronic Medical Record software in multiple languages to assist and improve longitudinal care. It is made available at no charge and is capable of running on GNU/Linux, Windows and Mac OS X. It is developed by a handful of medical doctors and programmers from all over the world. It can be useful to anyone documenting the health of patients including, but not limited to, doctors, physical therapists, occupational therapists ...

The R Project for Statistical Computing

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R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R."

AMIDE

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Amide's a Medical Imaging Data Examiner (AMIDE) is a completely free tool for viewing, analysing, and registering volumetric medical imaging data sets. It's been written on top of GTK+ , and runs on any system that supports this toolkit (Linux, Windows, Mac OS X with fink, etc.).

iHRIS Suite

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The iHRIS Suite of open source software supplies health sector leaders with information to track, manage, and plan the health workforce. Because the software is open source, it can be downloaded for free and customized for local needs. Each product addresses a specific health workforce leadership issue:

The 'epitools' R Package

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"epitools (epidemiology tools) is an R package for epidemiologic computing and graphics."

Lipsia

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Leipzig Image Processing and Statistical Inference Algorithms (Lipsia) is a software tool for processing functional magnetic resonance imaging (fMRI) data. It was developed over the course of several years at the Max-Planck-Institute for Human Cognitive and Brain Sciences in Leipzig, Germany.

The 'surveillance' R Package

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The R-package ’surveillance’ is a framework for the development and the evaluation of outbreak detection algorithms in univariate and multivariate routine collected public health surveillance data. Hence, potential users are biostatisticians, epidemiologists and others working in applied infectious disease epidemiology. However, applications could just as well originate from environmetrics, reliability engineering, econometrics or social sciences.

CTSim

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CTSim simulates the process of transmitting X-rays through phantom objects. These X-ray data are called projections. CTSim reconstructs the original phantom image from the projections using a variety of algorithms. Additionally, CTSim has a wide array of image analysis and image processing functions.

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