Extraction of medical knowledge from clinical data

In the last years, developed countries have faced the high incidence of many diseases that are increased significantly. The etiologies of those diseases are not clear and neither are the reasons for the increased number of cases. Early detection represents a very important factor in treatment and allows reaching a high survival rate. Due to the high volume of data to be read by physicians, the accuracy rate tends to decrease, and automatic reading and analyzing of digital data becomes highly desirable. In this paper, we discuss the problem of the high volume of medical data to be read by physicians, the accuracy rate tendency to decrease, and automatic reading of data that becomes highly desirable. The system is implemented and used against the data of the National Center for Health Statistics (NCHS) of the Centers for Disease Control and Prevention (CDC). From the generated association rules, we have found some interesting rules that can be used in the early prediction of health phenomenon.