0000000000546861
AUTHOR
Magí Lluch-ariet
On the Implementation of HealthAgents: Agent-Based Brain Tumour Diagnosis
This paper introduces HealthAgents, an EC-funded research project to improve the classification of brain tumours through multi-agent decision support over a secure and distributed network of local databases or Data Marts. HealthAgents will not only develop new pattern recognition methods for distributed classification and analysis of in vivo MRS and ex vivo/in vitro HRMAS and DNA data, but also define a method to assess the quality and usability of a new candidate local database containing a set of new cases, based on a compatibility score. Using its Multi-Agent architecture, HealthAgents intends to apply cutting-edge agent technology to the Biomedical field and develop the HealthAgents net…
Ranking of Brain Tumour Classifiers Using a Bayesian Approach
This study presents a ranking for classifers using a Bayesian perspective. This ranking framework is able to evaluate the performance of the models to be compared when they are inferred from different sets of data. It also takes into account the performance obtained on samples not used during the training of the classifiers. Besides, this ranking assigns a prior to each model based on a measure of similarity of the training data to a test case. An evaluation consisting of ranking brain tumour classifiers is presented. These multilayer perceptron classifiers are trained with 1H magnetic resonance spectroscopy (MRS) signals following a multiproject multicenter evaluation approach. We demonstr…