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.
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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.
HL7 file viewer, in tree-view format, with associated segment/field documentation. The latest release now includes editing, at all levels in the tree-view, e.g segment, field or component values. Purpose is for testing and bug-tracing HL7 communications.
The DHIS 2 is a tool for collection, validation, analysis, and presentation of aggregate statistical data, tailored (but not limited) to integrated health information management activities. It is a generic tool rather than a pre-configured database application, with an open meta-data model and a flexible user interface that allows the user to design the contents of a specific information system without the need for programming. DHIS 2 and upwards is a modular web-based software package built with free and open source Java frameworks.