The Development Of Supporting Information Management System For The Early Myocardial Ischemia Aided Diagnosis System Based On Deterministic Learning Theory

Myocardial ischemia, which is one of the most serious threats to people’s health, has become a common and frequently-occurring cardiovascular disease in the elderly. And its prevalence rate shows a rising trend year by year. Without treatment, myocardial ischemia can develop into exertional angina pain and myocardial infarction. If we find out myocardial ischemia in early stage and treat it in time, we can reduce the patients’ sudden death rate effectively. The typical symptoms of myocardial ischemia in clinical practice are changes of shape and amplitude of ST-T segment in electrocardiogram(ECG). However, the diagnosis of myocardial ischemia has some limitations through ECG.Based on deterministic learning theory, we can model and learn ST-T segment precisely. Then we can obtain the data of Cardiodynamicsgram(C DG) and show them in 3D visualization. Based on the calculation of Cardiodynamicsgram, we can obtain quantitative parameters, which can be used for early diagnosis of myocardial ischemia. It is beneficial for clinical popularization and application. However, there is no useful method to manage all those data in the diagnosis system. And the diagnosis method has been greatly restricted and restricted in clinical application and market promotion. Therefore, an efficient data management system is of great significance for early diagnosis of myocardial ischemia system.Aimed at above issues, we use SQ L Server to design the EC G information database management system. We use the index and the stored procedure to ensure the efficient performance of the system. And we realize the synchronization between the database systems. Based on MATLAB GUI and JDBC, we design the supporting information management system, which preliminary realize the efficient management of the patient’s medical records, ECG data information and modeling learning information. This management system is simple, user- friendly, and easier to contribute to generalized clinical application. So far, the ECG information database designed in this paper has collect 702 clinical patients information and 770 ECG records in FuWai Hospital of Beijing province. The system, which is featured by practicability, plays an important role in the early myocardial isc hemia aided diagnosis project. The system provides an effective way to study the results of the model analysis and the patient’s medical history information. The system has good practicability.