A general purpose neural network simulator system for medical data processing

We developed a general purpose neural network simulator system for medical data processing. This system has a flexible network definition language. Users can define arbitrary hierarchical neural networks using the definition language to analyze medical data that contains some complex patterns. The learning algorithm used in this system is back propagation. Learning curves are displayed on multiple windows. This is a general purpose system, so it can be used for various kinds of medical data processing such as one dimensional signal processing or two dimensional image processing. The system can run on a standard UNIX workstation, which is faster and more powerful than most personal computers. The system needs an X window system/Motif and C compiler. These are standard system programs already available on most UNIX workstations. The source code of the system can be retrieved from our anonymous ftp site via Internet.