A Prediction Model of Clinical Diagnosis by The Combination of Traditional Chinese and Western Medicine Based on Data Mining

To improve the single type of the existing clinical diagnosis and treatment decision support system, this paper proposes an intelligent medical diagnosis model of integrated TCM and Western medicine based on data mining. The scheme mainly inputs the diagnosis data into two subsystems for training and testing, according to the characteristics of the clinical diagnosis support information environment. Firstly, the improved Apriori algorithm is used to mine the TCM diagnosis and treatment data to obtain more perfect diagnosis information; then the BP neural network optimized by GA is adopted to process the real samples to improve the medical diagnosis speed. Finally, a clinical diagnosis prototype system combining the two methods is designed by customs clearance development, which is applied in the specific decision support and achieves good mining effect, and the prediction data is basically consistent with the clinical practice. Therefore, the scheme has been proved to be feasible and helpful to reduce clinical medical errors.