One very timely and cogent example of this is within the realm of Clinical Decision Support Systems (CDS). These systems are interactive computer programs designed to assist medical professionals in the analysis and diagnosis and provide greater health care options at a more cost effective rate. The raw data that is used is the knoweldge base -- raw statistics about populations, trends, demography, and individual indicators such as test results, measurments, vital statistics and symptomology. Then, the process moves into information in which the inference part of the program takes what may be disparate data and combines it into something that may have meaning for that particular situation or patient -- or may not -- thus saving medical personnel time pouring over chart data. Finally, usuing algorithims in machine learning (computers learn from past experiences and patterns) and artifical intelligence (computers make connections that were not always aapparent, the system delivers recommendations for general care, additional testing, and appropriate procedures. The power of the system is that it is useful as a guide, not as a replacement- there is still value judgement, subtle diagnosis issues, and experiential levels that a machine...

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Garg, Adhikari, McDonald, Rosas, Devereaux, and Beyene. (2005). Effects of Computerized Clinical Decision Support Systems on Practitioner Performance and Patient Outcomes. Jounral of the American Medical Association, 293(10), 1223-38.

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