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This paper presents a hierarchical classification system based on the k-Nearest Neighbors (kNN) classifier for classification of ten different classes of Malignant and Benign skin lesions from color image data. Our key contribution is to focus on the ten most common classes of skin lesions. Moreover, we use only high resolution color images acquired using a(More)
In this paper medical applications on a Grid infrastructure, the MAGIC-5 Project, are presented and discussed. MAGIC-5 aims at developing Computer Aided Detection (CADe) software for the analysis of medical images on distributed databases by means of GRID Services. The use of automated systems for analyzing medical images improves radiologists' performance;(More)
In this paper we present a comparative study among well established data mining algorithm (namely J48 and naive Bayes tree) and novel machine learning paradigms like ant miner and gene expression programming. The aim of this study was to discover significant rules discriminating ER+ and ER-cases of breast cancer. We compared both statistical accuracy and(More)
Background Array Comparative Genomic Hybridization has been successfully used in post-genomic cancer research studies [1,2]. In particular this technology has been developed in order to monitor gene copy number changes in whole DNA. Results returned by similar screening techniques are in the form of microarray high dimensional data; the data complexity(More)
Face recognition from an image or video sequences is emerging as an active research area with numerous commercial and law enforcement applications. In this paper different Pseudo 2-dimension Hidden Markov Models (HMMs) are introduced for a face recognition showing performances reasonably fast for binary images. The proposed P2-D HMMs are made up of five(More)
DNA microarray data are used to identify genes which could be considered prognostic markers. However, due to the limited sample size of each study, the signatures are unstable in terms of the composing genes and may be limited in terms of performances. It is therefore of great interest to integrate different studies, thus increasing sample size. In the(More)
This paper presents a novel approach to artificial neural network (ANN) topology optimisation that uses multi-objective genetic algorithm in order to find the best network configuration for the Wisconsin breast cancer database (WBCD) classification problem. The WBCD [Mangasarian, OL., et al., 1995][Mangasarian, OL., et al.][Wolberg, WH., et al., 1995] is a(More)
A unified evolutionary approach to coplanar radiotherapy inverse planning is proposed. It consists of a genetic algorithm-based framework that solves with little modification treatment planning for three different kinds of radiation therapy: conformal, aperture-based and intensity modulated. Thanks to evolutionary optimisation techniques we have been able(More)