Abstract Introduction Breast cancer is the most common cancer in women and one of the major causes of death from cancer among female around the world. The early detection and treatment are the major way to healing. The use of mammary thermography in Mastology is increasing as a complementary imaging technique to early detect lesions. Its use as a screening exam to identify breast disorders has been investigated. The aim of this study is to investigate the behavior of different classification methods while grouping the thermographic images into specific types of lesions. Methods To evaluate our proposal, we built classifiers based on artificial neural networks, decision trees, Bayesian classifiers, and Haralick and Zernike attributes. The image database is composed by thermographic images acquired at the University Hospital of the Federal University of Pernambuco. These images are clinically classified into the classes cyst, malignant and benign. Moments of Zernike and Haralick were used as attributes. Results Extreme Learning Machines (ELM) and Multilayer Perceptron networks (MLP) proved to be quite efficient classifiers for classification of breast lesions in thermographic images. Using 75% of the database for training, the maximum value obtained for accuracy was 73.38%, with a Kappa index of 0.6007. This result indicated to a sensitivity of 78% and specificity of 88%. The overall efficiency of the system was 83%. Conclusion ELM showed to be a promising classifier to be used in the differentiation of breast lesions in thermographic images, due to its low computational cost and robustness.

OBJETIVOS: avaliar e monitorar a implantação de um projeto voltado para a ampliação do acesso e a humanização do acolhimento aos usuários da rede básica de Salvador, entre novembro de 2005 e maio de 2008. MÉTODOS: foi realizada uma avaliação da implantação do projeto em três momentos, tanto de uma perspectiva externa, por equipe de consultores, quanto resultado de uma autoavaliação por parte dos Gerentes de Unidades. Com esse objetivo, foi elaborado um modelo lógico da intervenção, do qual foi derivada uma matriz com critérios para a avaliação. RESULTADOS: ao final do primeiro ano, a implantação dos componentes do programa variou entre 45% e 82% das unidades. Seis meses após, verificou-se uma ampliação da implantação. No terceiro e último ano, em 2008, avaliação feita em amostra de 24 Unidades revelou persistência da implantação do projeto, porém com importantes retrocessos. CONCLUSÕES: o elevado grau de implantação verificado, com a redução das filas evitáveis e melhoria da acessibilidade às unidades de saúde, no primeiro ano, pode estar relacionado à estratégia de implantação, bem como a algumas características da gestão municipal. Os autores discutem ainda as possíveis razões dos obstáculos encontrados no contexto da gestão municipal do Sistema Único de Saúde.

OBJECTIVES: to evaluate and monitor the implementation of a project aiming to broaden access and humanization of user embracement for users of the primary health care in Salvador, Brazil, between November 2005 and May 2008. METHODS: the implementation of the project was evaluated at three points in time, both externally, by a team of consultants, and internally as part of a self-evaluation by Unit Managers. An intervention logic model was designed for this purpose and a set of evaluation criteria derived from this. RESULTS: at the end of the first year, the implementation of program components varied from 45% to 82% of units. Six months later, implementation was more extensive. In the third and last year, in 2008, an evaluation carried out in a sample of 24 units revealed continued implementation of the project, albeit with a considerable setbacks. CONCLUSIONS: the high degree of implementation observed, with a reduction in the size of avoidable waiting queues and improvement in access to health units in the first year, may be related to the implementation strategy adopted and to some of the specific features of municipal administration. The authors also discuss the possible reasons for the obstacles encountered within the municipal administration of the Brazilian National Health System.