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Clinical engineering programs typically establish the content and frequency of a device's inspection and preventive maintenance procedures at the time of implementation. In some programs, these are not altered throughout the device's useful life. In others, history data and traditional statistical methods are used to adapt procedures to change in risk measures. Such methods are essentially reactive in that they are based upon past trends and do not readily consider potentialities for future change in the performance and utilization environments. Chaos theoretical concepts and related measures, when implemented in artificial intelligence programs such as neural networks and genetic algorithms, and used as an adjunct with computerized technology management programs, can assist in asking and answering the more dynamic, proactive questions necessary for effective inspection and preventive maintenance optimization. Today's healthcare environment is ideal for exploring their utilization.