DocumentCode :
3424797
Title :
Scopira: a pattern recognition application framework for biomedical datasets
Author :
Vivanco, Rodrigo A. ; Demko, Aleksander ; Pizzi, Nick J.
Author_Institution :
Inst. for Biodiagnostics, Nat. Res. Council Canada, Ottawa, Ont., Canada
fYear :
2005
fDate :
15-17 Dec. 2005
Abstract :
Machine learning techniques are widely used in the analysis of biomedical datasets. Modern devices tend to produce voluminous, high-dimensional datasets for which medical practitioners require high-performance, user-friendly programs and researchers need effective algorithm development and testing platforms. Interactive development systems, such as MATIAB, provide for rapid prototyping of algorithms and visualization but at the cost of computational efficiency. We present Scopira, a C++, open source programming framework for the development of biomedical data analysis applications.
Keywords :
C++ language; data analysis; learning (artificial intelligence); medical computing; parallel programming; pattern recognition; public domain software; C++ programming; Scopira; biomedical dataset analysis; biomedical datasets; high-performance user-friendly programs; interactive development systems; machine learning; open source programming; pattern recognition application; voluminous high-dimensional datasets; Application software; Biomedical imaging; Computational efficiency; Data analysis; Data visualization; MATLAB; Machine learning; Machine learning algorithms; Pattern recognition; Prototypes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications, 2005. Proceedings. Fourth International Conference on
Print_ISBN :
0-7695-2495-8
Type :
conf
DOI :
10.1109/ICMLA.2005.55
Filename :
1607446
Link To Document :
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