Zouiten Mohammed
ABSTRACT
Two-dimensional arrays of bi-component structures made of cobalt and permalloy elliptical dots with thickness of 25 nm, length 1 m and width of 225 nm, have been prepared by a self-aligned shadow deposition technique. Brillouin light scattering has been exploited to study the frequency dependence of thermally excited magnetic eigenmodes on the intensity of the external magnetic field, applied along the easy axis of the elements. Our work is part of user-centered healthcare decision-making systems based on a process of predicting cancer distribution. This process should lead to a set of knowledge in Datamining, Ontologies and Geographical Information Systems. It is in the same time iterative and interactive. Therefore, it seems essential to take into account principles and methods of Human-Machine Interaction in the development of such systems. In this respect, development of interactive decision-making systems is currently being approached using two opposing approaches. In the first one, technology is fundamental; the second one is user centered placing the human actors in a central position. Although the first approach is still present in healthcare organizations, the current trend is definitely the user centric. In our framework we propose an approach that aims to integrate the steps of the predicting future from data process into a development model enriched from human-machine interactions. Our application context is the fight against breast cancer in hospitals. We demonstrate that medical decision can be based on a spatial analysis of the geographical distribution of many cancers. Several factors explain our choice of datamining for assistance of health decision-makers for learning in the CART algorithm about patients who are future actors of suspicion.
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Index Terms
- Machine learning algorithms for oncology big data treatment
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