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Mining accompanying relationships between diseases from patient records

In order to increase the understanding of diseases, research on relationships among diseases becomes popular nowadays. Several previous works focus on finding the relationships between diseases from genomes. However, the relationships between diseases are also affected by many other factors such as gender, age, and even seasons. In this work, we divide patients into several groups, based on their genders and ages. After that, we find the relationships between diseases in the distinct groups from patient records. For example, in a group of middle-aged men, we find a significant percentage of patients getting a disease after a specified disease in a time period. Association rule mining is adopted to find the relationships of diseases. The relationships between diseases found can be applied to many fields, such as health education for people and information for researchers.