Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.

Logificação da Psicologia o itinerário intelectual de Edmundo Curvelo sobre a Mente, a Lógica e a Filosofia

Tese de Doutoramento em Filosofia - Especialidade de Filosofia da Mente

A emergência da matemática em situações de jogo no jardim de infância e na creche

Relatório de estágio de mestrado em Educação Pré-Escolar

Bases de Gröbner e geração de exercícios matemáticos com estrutura não determinada

Definido um enredo concreto, há, frequentemente, uma grande quantidade e variedade de exercícios que sobre ele podemos escrever. Neste artigo, apresenta-se um algoritmo que permite automatizar este processo. Para gerar exercícios matemáticos, parte-se das relações entre as variáveis presentes no enredo, calcula-se os possíveis exercícios, analisa-se a complexidade do seu processo de resolução e a sua viabilidade. O algoritmo recorre a bases de Gröbner para determinar se o exercício é resolúvel e um possível caminho de resolução. Com base na análise dos resultados obtidos, torna-se possível criar uma base de exercícios ligada a esse enredo.

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

O livro na revista: como revistas semanais brasileiras e portuguesas abordam livros e literatura

Dissertação de mestrado em Comunicação, Arte e Cultura

Materializar afetos: entre universos e registos da memória familiar burguesa e os seus usos sociais

Dissertação de mestrado em História

On modified simple reacting spheres kinetic model for chemically reactive gases

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