Learning First-Order Rules to Handle Medical Data

Since information systems are used in large hospitals, a large amount of medical data is provided to physicians which often constitutes an information overload. Consequently, computers must extract useful information from such data. The most difficult issue in handling medical data is that included time-series data have irregularities. Here, we describe handling this type of data using a first order logic learning system named DAMS.