Improving Case-Based Reasoning Systems by Combining K-Nearest Neighbour Algorithm with Logistic Regression in the Prediction of Patients’ Registration on the Renal Transplant Waiting List

摘要

IntroductionCase-based reasoning (CBR) is an emerging decision making paradigm in medical research where new cases are solved relying on previously solved similar cases. Usually, a database of solved cases is provided, and every case is described through a set of attributes (inputs) and a label (output). Extracting useful information from this database can help the CBR system providing more reliable results on the yet to be solved cases.