Architecture of a neural network client/server system for decision support in clinical information systems

Neural networks have demonstrated their research potential in bio-medical sciences. The literature is filled with experiments that evidence the value of neural networks for the solution of diagnostic and predictive problems. The next step is to direct research efforts toward implementation of these neural networks into the clinical information environments where their diagnostic and predictive capabilities can be truly utilized. To accomplish this goal, it is necessary to create a new generation of neural network tools that ease the transition of experimental results to a production state. This paper describes the architecture of such a system.