Abstract

How to solve diagnosis problem effectively by the aid of Artificial Intelligence has been being a focus of Intelligent System researching and development. However, performance of the native Uncertainty Reason method still is unsatisfactory to professionals and researchers. This paper proposes the concept of Pivot-Association Factor and its Certainty Index Correction algorithm, and on this base designs an innovative AI method for solving disease diagnosing. By the prototype system of the novelty diagnosing algorithm, researcher team practises a series of test experiments. Results and analysis demonstrate that the method exhibit a better diagnosing efficiency than man-expert individual and the native Certainty Factor Diagnosing Method. On the whole, it manifests an accurate rate of diagnosis over 82% and possesses the capacity to expand diagnosing capability of man-expert.

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