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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.

cancer Biomedical Informatics Grid (caBIG)

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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.

Insight Segmentation and Registration Toolkit (ITK)

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ITK is an open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both.

The 'epibasix' R Package

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This package contains elementary tools for analysis of common epidemiological problems, ranging from sample size estimation, through 2x2 contingency table analysis and basic measures of agreement (kappa, sensitivity/specificity).

Appropriate print and summary statements are also written to facilitate interpretation wherever possible.

This package is a work in progress, so any comments or suggestions would be appreciated. Source code is commented throughout to facilitate modification. The target audience includes graduate students in various epi/biostatistics courses.

OpenEMed

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OpenEMed is a set of distributed healthcare information service components built around the OMG distributed object specifications and the HL7 (and other) data standards and is written in Java for platform portability. We emphasize the interoperable service functionality that this approach provides in reducing the time it takes to build a healthcare related system. It is not intended as a turnkey system but rather a set of components that can be assembled and configured to meet a variety of tasks.

Aurion

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Aurion is an open source health information exchange platform that implements the Nationwide Health Information Network standard services and content specifications. Aurion is the first project chartered through the Alembic Foundation. This software enables the secure exchange of interoperable health information among diverse organizations using a wide variety of technologies.

ADDIS

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ADDIS is a software developed within the Dutch Escher-project for managing and analyzing clinical trial information.

ADDIS is a proof-of-concept system that allows us to simultaneously discover the possibilities of and the requirements on a database of structured clinical trials data. The automated discovery and (meta-)analysis of trial data, as well as benefit-risk assessment is supported.

ADDIS comes with two built-in examples:

Dcm4che

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dcm4che is a collection of open source applications and utilities for the healthcare enterprise. These applications have been developed in the Java programming language for performance and portability, supporting deployment on JDK 1.4 and up.

At the core of the dcm4che project is a robust implementation of the DICOM standard. The dcm4che-1.x DICOM toolkit is used in many production applications across the world, while the current (2.x) version of the toolkit has been re-architected for high performance and flexibility.

Chiapas

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Chiapas is an enterprise level HIPAA data translation package. It supports all major healthcare transactions and a variety of SQL databases and file types, and incorporates a script parser and a GUI studio for development and maintaining specifications.

The 'epicalc' R Package

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Functions making R easy for epidemiological calculation.

Datasets from Dbase (.dbf), Stata (.dta), SPSS(.sav), EpiInfo(.rec) and Comma separated value (.csv) formats as well as R data frames can be processed to do make several epidemiological calculations.

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