The 'epitools' R Package
"epitools (epidemiology tools) is an R package for epidemiologic computing and graphics."
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"epitools (epidemiology tools) is an R package for epidemiologic computing and graphics."
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.
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.
STIR is Open Source software for use in tomographic imaging. Its aim is to provide a Multi-Platform Object-Oriented framework for all data manipulations in tomographic imaging. Currently, the emphasis is on (iterative) image reconstruction in PET, but other application areas and imaging modalities can and might be added.
STIR is the successor of the PARAPET software library which was the result of a (European Union funded) collaboration between 6 different partners (see Credits).
The dinifti program converts MRI images stored in DICOM format to NIfTI format.
The Epi package is mainly focused on "classical" chronic disease epidemiology. The package has grown out of the course Statistical Practice in Epidemiology using R.
Grassroots DICOM (GDCM) is an implementation of the DICOM standard designed to be open source so that researchers may access clinical data directly. GDCM includes a file format definition and a network communications protocol, both of which should be extended to provide a full set of tools for a researcher or small medical imaging vendor to interface with an existing medical database.
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.
Niftilib is a set of i/o libraries for reading and writing files in the nifti-1 data format. nifti-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images.
Niftilib currently has C, Java, MATLAB, and Python libraries; we plan to add some MATLAB/mex interfaces to the C library in the not too distant future.
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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