Evaluation of Case Based Reasoning for Clinical Decision Support Systems applied to Acute Meningitis Diagnose

This work presents a research about the applicability of Case Based Reasoning to Clinical Decision Support Systems (CDSS), particularly applied to the diagnosis of the disease known as Acute Bacterial Meningitis. In the last few years, the amount of information available to the medical doctor, who usually finds himself in the situation of making a diagnosis of one or more diseases, has dramatically increased. However, the specialist’s ability to understand, synthesize and take advantage of such information in the alwayslittle time during the medical act remains to be developed. Many contributions have been made by the computer sciences, especially those by Artificial intelligence, in order to solve these problems. This work focuses on the diagnose of the Acute Bacterial Meningitis, and carries out a comparative assessment of the quality of a Clinical Decision Support System made through Case Based Reasoning, in contrast to an already existing CDSS applied to the same task, but developed using a technique called Bayesian expert system.