Knowledge discovery in health domain using deep neural network algorithms

With the nowadays technology and the plenty of information in the health care system, there is a need to extract a useful knowledge that can be used to diagnose and identify patterns in the patient records. The process to extract such knowledge is called data mining. The steps of pattern extraction and discovery involve a complex process, which normally uses a large amount of datasets. There are several application and systems implemented to diagnosis patient records in health care and clinical data. One of them is called the knowledge discovery in database (KDD) which mostly depends on developing a method that can process the data in a good manner. Data mining steps are considered one of crucial steps in KDD process in order to extract a useful pattern from the dataset. In order to achieve better healthcare services, data mining requires a proper design and implementation of data mining algorithm to identify a unique pattern from the data. In this research we suggest using Patient Information for the Hewa Hospital in Sulamani, which is responsible for the cancer and blood decease as a case study. The main aim of this study is to investigate the deep neural network (DNN) and Artificial neural network (ANN) as classification algorithms in order to help us for better decisions.