الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
There have been rapid developments in medical sciences all over the world, during the recent years. There is a continuous increases in the traditional medical knowledge, means (scientific magazines, e-books, and even the internet new generations, etc.). So, it is difficult, for physicians to regularly follow all recent innovations during a patient’s visit. Medical informatics can play an important role in improving patient-centered care by developing Decision Support Systems to support the inclusion of patient expectations in clinical decision making. The thesis contributed new results in the area of intelligent medical Decision Support System. We build medical Decision Support System for neurosurgical unit at Mansoura New General Hospital. It based on a hybrid approach, which is a combination of rapid learning approach, evidence-based medicine, and shared decision making approaches, to improve the predictability of outcome. The decision will be made based on latest scientific research, clinical pathways, and patient expectations. So, it will be suitable for continuous development and new trends in medical field. In the knowledge phase, we use the rough set theory which is particularly useful for discovering relationships in data, the data mining aspect of rough sets can be regarded as a technique of machine learning. Also, we develop Rough Set Reduction (ROSER) software to classify the empirical data and subsequent decision making.