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.

Social entrepreneurship: does institutional environment make a difference?

The purpose of this paper is to contribute to a better understanding of the link between social entrepreneurs and institutional environment in Portugal. A quantitative approach is used in the study, and primary data were collected through an online survey. A questionnaire was emailed to, both, Portuguese Non-Governmental organizations and projects available on the Portuguese social stock exchange. In the analysis of the data were used descriptive statistics, factorial analysis and t-student tests to validate (or not) the research hypotheses. The results show that a favorable institutional environment has a low importance in the decision to develop social initiatives. This conclusion supports the idea that many social entrepreneurs can emerge even in developing regions where the institutional environment is weak. Therefore, social entrepreneurship could be an instrument of regional development and contribute to attenuate the social and economic differences among Portuguese regions.