The Research And Application Of The Data Processing Technique In Anesthesia Inspection

The degree of the patients' narcotism caused by narcotic in the surgery is important index for anesthetists to supervise. With an appropriate degree of anesthetization, the patients will feel painless and suffer the least hazard caused by anesthesia. Currently, the anesthetists usually observe the changes of the patient's clinical signs and during the surgery to evaluate the degree. But the results are often influenced by the experience and skill of the anesthetists . Meanwhile, they are often postponed because the changes observed by anesthetists are in fact results of improper degree. Modern surgery generates huge amounts of data. How to analyze these data to find valuable knowledge and principle has become a hot spot in knowledge discovery.The paper describes the application and research of artificial neural networks (ANN), the important way of knowledge discovery, in the inspection of anesthetization degree. Firstly, the paper discusses the process, object and method of knowledge discovery, then introduces the anesthetization case database, the ANN model and the evaluation about the result. Finishes the job using a three-step knowledge discovery process: (1) Designing of the anesthetization case database. (2) Designing and training of the ANN model. (3) Using the ANN model to inspect the sample case of anesthetization, evaluating the result. Finally draw a conclusion that, using the heart rate and blood pressure as the input of the ANN model, we can get the better classification of anesthetization degree than using the traditional method and the method of the ANN model is more practical than those laboratorial methods. The paper also provides a mature protocol and preparation of data in the knowledge discovery of anesthetization.