EGADSS (Evidence-based Guideline and Decision Support System) is an open source tool that is designed to work in conjunction with primary care Electronic Medical Record (EMR) systems to provide patient specific point of care reminders in order to aid physicians provide high quality care. EGADSS is designed as a stand alone system that would respond to requests from existing Electronic Medical Records such as Wolf, Med Access, and MedOffIS to provide patient specific clinical guidance based on its internal collection of guidelines.
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Occupancy in certain hospital patient care units is impacted by procedure scheduling policies and practices. For example, intensive care unit occupancy is strongly related to open heart surgery schedules. Similarly, occupancy in obstetrical postpartum units is impacted by the daily number of scheduled labor inductions and cesarean sections. That was the motivation for this project.
OBsched is a set of optimization models and supporting software for exploring the relationship between patient scheduling and nursing unit occupancy in hospitals.
A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectral analysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.
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.
Brainstorm is a collaborative open-source Matlab application dedicated to magnetoencephalography (MEG) and electroencephalography(EEG) data visualization, processing and cortical source estimation.
The intention is to make a comprehensive set of tools available to the scientific community involved in MEG/EEG experimental research.
For physicians and researchers, the interest of this software package resides in its rich and intuitive graphic interface, which does not require any programming knowledge.
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.
HAPI (HL7 application programming interface; pronounced "happy") is an open-source, object-oriented HL7 2.x parser and encoder for HL7 version 2.x messages written in Java. This project is not affiliated with the HL7 organization; we are just writing some software that conforms to their specification. The project was initiated by University Health Network (a large multi-site teaching hospital in Toronto, Canada).
This project provides a simple but flexible Perl Toolkit for using the HL7 protocol. The toolkit consists of a Perl API, an implementation of a pluggable forking HL7 server, and an HL7 message queue daemon for developing HL7 capable applications in Perl.
REMITT is a revolutionary medical information translation and transmission system, which is primarily used for preparing and submitting medical billing data.
REMITT works independent of any specific electronic medical record (EMR) or practice management (PM) system, and can interface with any EMR or PM system which implements its application programming interface (API). The first system to do so has been FreeMED.
Currently Supported Formats
- ANSI NSF X12 837 Professional
Currently Supported Output Types
Leipzig Image Processing and Statistical Inference Algorithms (Lipsia) is a software tool for ficken 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.