eXiT*CBR.v2: Distributed case-based reasoning tool for medical prognosis

Abstract

In this work we propose a user-friendly medically oriented tool for prognosis development systems and experimentation under a case-based reasoning methodology. The tool enables health care collaboration practice to be mapped in cases where different doctors share their expertise, for example, or where medical committee composed of specialists from different fields work together to achieve a final prognosis. Each agent with a different piece of knowledge classifies the given cases through metrics designed for this purpose. Since multiple solutions for the same case is useless, agents collaborate among themselves in order to achieve a final decision through a coordinated schema. For this purpose, the tool provides a weighted voting schema and an evolutionary algorithm (genetic algorithm) to learn robust weights. Moreover, to test the experiments, the tool includes stratified cross-validation methods which take the collaborative environment into account. In this paper the different collaborative facilities offered by the tool are described. A sample usage of the tool is also provided.

Intelligent Decision Support Systems

“…Case-based reasoning is a knowledge-based methodology which allows a problem to be solved based on past experiences (Aamodt and Plaza 1994). Case-based reasoning seeks cases similar to the current one and analyses which decision or classification was taken in order to reuse it in the present solution (Pla et al 2013). CBR Systems solve problems by using knowledge gained from solving similar problem in the past.…”

When Collective Knowledge Meets Crowd Knowledge in a Smart City: A Prediction Method Combining Open Data Keyword Analysis and Case-Based Reasoning

“…The Compaq SMART system was developed and applied using CBR to support the Compaq help desk [27]. Particularly relevant to this study is the fact that many CBR systems have been applied in medical decision making, such as CBR for medical knowledge-based systems [28], CBR in the health sciences [29], CBR for the prognosis and diagnosis of chronic diseases [30], case-based medical diagnosis, development, and experimentation [31], and a distributed CBR tool for medical prognosis [32]. Recently, CBR has been applied in problem-solving complex domains, including planning [33], law [34], e-learning [35], knowledge management [36], image processing [37], and recommender systems [38].…”

Generating project risk response strategies based on CBR: A case study

“…Some studies in recent years show that it is feasible to solve the decision-making problems using the case-base decision analysis methods (Amailef & Lu, 2013;Chen, Kilgour, & Hipel, 2008;Ma, 2012;Pla, López, Gay, & Pous, 2013). Thus, to solve the project risk response problem, a way of case-base decision analysis may be considered.…”