A Classification Canvas for the analysis of biomedical data

Abstract

With the rapid proliferation of complex high-dimensional biomedical data, an acute need exists for a comprehensive, knowledge-based, domain-specific, user-friendly software suite that allows investigators, in the health care disciplines, to classify their data through the detection of novel or discriminating features therein. The Classification Canvas is an attempt to achieve these goals in addition to providing intuitive visual computation and logic construction. In this paper we describe various design and implementation issues such as: balancing user (novice) friendliness and developer (experienced) utility, performance versus modularity trade-offs, C++ and Java data sharing responsibilities, and creating graphical interfaces for (user-supplied) algorithm control.