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.
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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.
3D medical image platform for visualization and image processing. Segmentation with Levels sets. Surface reconstruction with marching Cubes, texture Mapping and Raycasting, DICOM support.
Photograph, manage, view, compare, document healing processes and archive digital pictures fully integrated into doctor's practice systems. Take a photo and immediately see how the picture gets archived to your current patient automatically.
FW4SPL is a component-oriented architecture with the notion of role-based programming. FW4SPL consists of a set of cross-platform C++ libraries. For now, FW4SPL focuses on the problem of medical images processing and visualization.
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.
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.
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 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.