Based on associated-key-factor's-forecasting and machine learning Bayes disease diagnostic algorithm
Guoqiang Guo · Jisuanji gongcheng yu sheji · 2008
To slove disease diagnosis problem,concept of associated-key-factor and its reliability forecast algorithm are proposed,while weighting forecast inference and the machine statistics learning method are designed,both of which suitable for the subjective Bayes rule.In view of multi-rule activation,the score-coefficient-integration and analogy of union-set are designed to simulate expert-doctors con-sultation.Experiments indicated that,reliability forecast method enhanced the machine diagnosis coincidence rate,and integration method synthesized the multi-diagnosis conclusion reasonably,then the effect is good.