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1.
Comput Methods Programs Biomed ; 83(2): 157-67, 2006 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-16893587

RESUMO

In this paper, we present Microarray Medical Data explorer (Microarray-MD), a novel software system that is able to assist in the exploratory analysis of gene expression microarray data. It implements a combination scheme of multiple Support Vector Machines, which integrates a variety of gene selection criteria and allows for the discrimination of multiple diseases or subtypes of a disease. The system can be trained and automatically tune its parameters with the provision of pathologically characterized gene expression data to its input. Given a set of new, uncharacterized, patient's data as input, it outputs a decision on the type or the subtype of a disease. A graphical user interface provides easy access to the system operations and direct adjustment of its parameters. It has been tested on various publicly available datasets. The overall accuracy it achieves was estimated to exceed 90%.


Assuntos
Expressão Gênica , Análise de Sequência com Séries de Oligonucleotídeos/métodos , Software , Neoplasias do Colo/genética , Humanos , Masculino , Neoplasias da Próstata/genética
2.
Comput Methods Programs Biomed ; 70(2): 151-66, 2003 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-12507791

RESUMO

In this paper, we present CoLD (colorectal lesions detector) an innovative detection system to support colorectal cancer diagnosis and detection of pre-cancerous polyps, by processing endoscopy images or video frame sequences acquired during colonoscopy. It utilizes second-order statistical features that are calculated on the wavelet transformation of each image to discriminate amongst regions of normal or abnormal tissue. An artificial neural network performs the classification of the features. CoLD integrates the feature extraction and classification algorithms under a graphical user interface, which allows both novice and expert users to utilize effectively all system's functions. It has been developed in close cooperation with gastroenterology specialists and has been tested on various colonoscopy videos. The detection accuracy of the proposed system has been estimated to be more than 95%. As it has been resulted, it can be used as a supplementary diagnostic tool for colorectal lesions.


Assuntos
Colonoscopia/métodos , Neoplasias Colorretais/diagnóstico , Diagnóstico por Computador/métodos , Algoritmos , Colonoscopia/estatística & dados numéricos , Humanos , Processamento de Imagem Assistida por Computador , Pólipos Intestinais/diagnóstico , Redes Neurais de Computação , Lesões Pré-Cancerosas/diagnóstico , Design de Software , Interface Usuário-Computador , Gravação de Videoteipe
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