You are here

Home » Analysis » Data Analysis » Cross-platform

Project Wizard

You can use the category filters given on the right sidebar to narrow down your search results.

Laika

Rating: 
Your rating: None Average: 3.5 (4 votes)

Laika analyzes and reports on the interoperability capabilities of EHR systems. This includes the testing for certification of EHR software products and networks.

To support EHR data interoperability testing, Laika is designed to verify the input and output of EHR data against the standards and criteria identified by the Certification Commission for Health Information Technology (CCHIT). Laika is used by the Certification Commission to perform part of the interoperability certification inspection of EHRs.

Homepage: 
http://laika.sourceforge.net/

PyMVPA

Rating: 
Your rating: None Average: 3.7 (3 votes)

"PyMVPA is a Python module intended to ease pattern classification analyses of large datasets. In the neuroimaging contexts such analysis techniques are also known as decoding or MVPA analysis. PyMVPA provides high-level abstraction of typical processing steps and a number of implementations of some popular algorithms. While it is not limited to the neuroimaging domain, it is eminently suited for such datasets. PyMVPA is truly free software (in every respect) and additionally requires nothing but free-software to run."

Homepage: 
http://www.pymvpa.org/

EGADSS

Rating: 
Your rating: None Average: 2.1 (11 votes)

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.

Homepage: 
http://egadss.sourceforge.net/

OBsched

Rating: 
Your rating: None Average: 1 (2 votes)

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.

Homepage: 
http://www.hselab.org/projects/obsched/

PyEEG

Rating: 
Your rating: None Average: 2 (4 votes)

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.

Homepage: 
http://code.google.com/p/pyeeg/

WEKA

Rating: 
Your rating: None Average: 2.7 (3 votes)

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.

Homepage: 
http://www.cs.waikato.ac.nz/ml/weka/

rxncon

Rating: 
Your rating: None Average: 5 (2 votes)

The complexity of cellular networks is an outstanding challenge for documentation, visualisation and mathematical modelling. In this project, we develop a new way to describe these networks that minimises the combinatorial complexity and allows an automatic visualisation and export of mathematical (ODE/rulebased) models.

Features:

  • Automatic visualiztion with Cytoscape.
  • Automatic generation of rule based models for BioNetGen.
  • Storage of biological facts that can be used for modelling.
Homepage: 
http://www.rxncon.org/

ACHILLES

Rating: 
No votes yet

ACHILLES is a platform which enables the characterization, quality assessment and visualization of observational health databases. ACHILLES provides users with an interactive, exploratory framework to assess patient demographics, the prevalence of conditions, drugs and procedures, and to evaluate the distribution of values for clinical observations.

ACHILLES is intended to be implemented by organizations that have patient-level observational health databases available in their local environment.

Homepage: 
http://www.ohdsi.org/analytic-tools/achilles-for-data-characterization/

ParaView

Rating: 
Your rating: None Average: 4 (1 vote)

ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView's batch processing capabilities.

ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of terascale as well as on laptops for smaller data.

Homepage: 
http://www.paraview.org/
Displaying 1 - 10 of 10 projects that are relevant to your search query.