Design And Implementation Of An Auxiliary Diagnostic System For Jaundice

As we all know,the process of disease diagnosis is based on the patient's clinical symptoms,combined with their own medical knowledge to make a judgment of the cause of the process.Clinical symptoms mentioned here are broad,symptomatic,experimental,signs and a variety of tests,clinicians through a comprehensive analysis,an important basis to judge.Subjective factors have a greater impact on this diagnostic program,the diagnosis is correct and the doctor's medical level is closely related.In order to help clinicians to comprehensively consider the diagnostic results,and can eliminate various human factors and get objective and accurate diagnosis results,this paper presents an auxiliary diagnostic system for jaundice diseases,which can help physicians according to the existing clinical Symptoms,the disease comprehensively and scientifically correct diagnosis of the disease,thereby further improving the diagnostic accuracy.According to the suggestions and opinions of medical experts,this article summarizes the pathological and case knowledge of jaundice diseases,and uses the machine learning classification algorithm to process the clinical symptoms knowledge and data.The main work is as follows:(1)Combined with the clinical practice of jaundice to be investigated in the medical field of knowledge and experts in the diagnosis of jaundice disease experience based on the common jaundice to be investigated to be summarized(such as hepatitis A,cirrhosis,pancreatic cancer,non-alcoholic fat Liver disease,drug jaundice and other 20 kinds of diseases);for each disease etiology,diagnosis in-depth study,the establishment of clinical symptoms of knowledge base.(2)Research on the classification algorithm in machine learning,such as logical regression,decision tree classification,Bayesian network and support vector machine.(3)Preprocessing and characterizing all the data,and classifying the characteristic data of these 20 diseases,classifying the decision tree and classifying the Bayesian classification,and optimizing the parameters and comparing the results.(4)According to the actual situation of jaundice disease diagnosis,the auxiliary diagnosis system of jaundice disease is developed in ubantul4 development environment and python development language.The system consists of data preprocessing module,classifier building module and interface module.