Search Results for "java medical imaging"
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Showing 21 open source projects for "java medical imaging"
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OpenMRS
Open source Health IT for the planet
OpenMRS is a community-developed, open source, enterprise electronic medical record system. Our mission is to improve health care delivery in resource-constrained environments by coordinating a global community to creates and support this software. -
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Gpf4Med
Graph Processing Framework for Medical Information
Gpf4Med is a graph processing framework for clinical data, which can leverage from previously existing medical database and Cloud computing facilities to address large-scale studies. -
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MetaCoDe is an open source project which purpose is the automated semantic tagging of medical texts, based on the UMLS metathesaurus. Targeted languages are French and English languages in the first time.
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A cross-platform Java program to turn a simple Geiger counter into the equivalent of a state-of-the art digital model, plus some – using your laptop computer.
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EEG-Holter - Designed for analysis of long-term EEG - Holter. Java developed, it supports medical and logbook anotations, epileptic events data, graphics and EDF files. UNIFESP © 2009 - Aristides Tavares dos Santos, Prof. Dr. Carlos J R Campos.
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QSAR is a project that aims to build a GUI that enables people to build quantitative structure activity (or property) relationship models. It will use parts of CDK (cdk.sf.net), JOELib (joelib.sf.net), R (www.r-project.org) and other projects.
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Java GUI to analyze one (or more, in batch mode) datasets with several feature selection methods at the same time and also performing an "ensemble" analysis. It can be easily extended to include any feature selection algorithm.
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SciBearSpace
Clinical Information Management
Open Source Clinical Information Management System. From research to laboratory. Gathering / storing of analytical data within an SQL database. -
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A Trial Workbench for Facilitating Best Practices from Prospective to Acute Care in Respiratory Medicine. We aim to provide a set of information management toolboxes that facilitates decision support applications in medical information systems.
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FORce based Cluster Editing (FORCE) is a Java software heuristically solving the graph cluster editing problem on weighted edges using BLAST E-values. It further provides a training mode for heuristic parameter estimation.
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Evidence-based Guideline and Decision Support System. Provides patient specific point of care reminders in order to aid physicians provide high quality care. Input/output in the form of HL7 CDA Level 2 documents. Knowledge is encoded using Arden Syntax.
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Thea, Tools for High-throughput Experiment Analysis, is an integrated information processing system dedicated to the annotation of data issued from classification systems with biological information coming from a knowledge base.
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MicroArray Genome Imaging and Clustering Tool (MAGIC tool) is a platform-independant java program for analyzing MicroArray data (.tiff scans & .txt godlists) via graphs and clustering operations (including QT-clustering). http://www.bio.davidson.edu/magic
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OpenClinics is a software platform for the collection, maintainance and analysis of medical, (primarily disease-based), information for use by medical clinics worldwide.
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Sight provides a friendly interface to create and connect agents for bioinformatics. The workflow supports multiple responses to a single request, structure transforms, filters and request history access.Can talk with ordinary http servers (get and post)
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Pattern recognition system written in Java. Provide statistical informations about satellite and medical imagery; and also recognize symbols in a gaussian blur.
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NeoBio is a Java class library of Computational Biology Algorithms. The current version consists mainly of pairwise sequence alignment algorithms such as the classical dynamic programming methods of Needleman-Wunsch and Smith-Waterman.
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A java based neural network framework. The Auratus network is built around an XML messaging system, allowing for a complete MVC design. Additionally, Auratus networks are constructed and at the node/edge level, allowing for advanced topologies.
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