title: A pattern recognition application framework for biomedical datasets.
abstract: Scopira facilitates the development of high-performance applications by providing many useful subsystems, flexible and efficient data models, low-level tools such as memory management and serialization, GUI constructs, high-level visualization modules, and the ability to implement parallel algorithms with MPI. Scopira plug-in extensions have been developed to enable Matlab scripts to easily call any Scopira module, thus facilitating the migration of prototypes to highly efficient C++ applications. Scopira is continuously under development and future capabilities will include the ability to develop distributed programs using agents, applicable to grid-computing data mining applications. Scopira has proven to be a successful programming framework for implementing high-performance biomedical data analysis applications. It is based on C++, an efficient object-oriented language, and the source code is available as an open-source project for other researchers to use and adapt to their own research endeavours. Scopira has been compiled to work on Linux and Windows XP operating systems with a port to the Mac OS under development. Scopira, EvIdent and RDP are freely available for download from www.scopira.org.
authors: National Research Coucil, Institute for Biodiagnostics, Canada. rodrigo.vivanco@nrc-cnrc.gc.ca
authors: Rodrigo
authors: R
authors: Vivanco
authors: Aleksander B
authors: AB
authors: Demko
authors: Mark
authors: M
authors: Jarmasz
authors: Ray L
authors: RL
authors: Somorjai
authors: Nick J
authors: NJ
authors: Pizzi
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001698:Biomedical Engineering / Q000379:methods; D003628:Database Management Systems; D016208:Databases, Factual; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity