id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_y6kn666wmrc5xidvufq5vk6rfu	Rosanne Janssen	Case-based reasoning for predicting the success of therapy	2014	14	.pdf	application/pdf	9926	1031	73	Case-based Reasoning for Predicting the Success of Case-based reasoning for predicting the success of therapy Case-based reasoning for predicting the success of therapy predicting the effect of treatments for patients with anxiety disorders. Keywords: case-based reasoning, prediction, forecasting-by-analogy, weighted voting, information gain, nearest neighbour method, accuracy, mental health care, treatment outcome, anxiety disorders In this study, we aim to use case-based reasoning (CBR) to make treatment predictions, a CBR system called CBRth the values of these nominal and ordinal features as scores, the casebase (Section 3.3) but also cases of patients that Table 1: Features used in case-based reasoning therapy For CBRth, we use CBR to predict in which class a new values of the Cl. The prediction for the target case is the Figure 4: Results case-based reasoning therapy with K = max 1. CBRth with the gain as feature weight gives better results. predictions are based on more similar cases.	./cache/work_y6kn666wmrc5xidvufq5vk6rfu.pdf	./txt/work_y6kn666wmrc5xidvufq5vk6rfu.txt