The presence of microcalcification clusters in mammograms contributes evidence for the detection of early stages of cancer. In this paper, a low-cost and high-speed neural network based breast cancer detection algorithm is presented. The microcalcifications are extracted with an adaptive neural network that is trained with cancer/malignant and normal/benign breast mammograms and a best accuracy...

The standard prediction process of SVM requires acquisition of all the feature values for every instance. In practice, however, a cost is associated with the mere act of acquisition of a feature, e.g. CPU time needed to compute the feature out of raw data, the dollar amount spent for gleaning more information, or the patient wellness sacrificed by an invasive medical test, etc. In such applicat...

network location models comprise one of the main categories of location models. these models have various applications in regional and urban planning as well as in transportation, distribution, and energy management. in a network location problem, nodes represent demand points and candidate locations to locate the facilities. if the links network is unchangeably determined, the problem will be ...

In recent years there is an increasing interest for analytical methods that learn patterns over large-scale data distributed over Peer-to-Peer (P2P) networks and support applications. Mining patterns in such distributed and dynamic environment is a challenging task, because centralization of data is not feasible. In this paper, we have proposed a distributed classification technique based on Re...