The aim of this paper is to illustrate how statistical tools can benefit healthcare policy makers specialised in the rabies management. Understanding the prevalence of such a disease is crucial for management teams. Seasonality may be a salient feature of data series provided by medical units, that is why the use of an innovative tool for seasonal adjustment is needed. For this paper, the data series (number of persons examined for rabies, by age and residency) were provided by one single health care unit – The National Institute of Infectious Diseases “Matei Bals”.

A company's environment is constantly changing, new competitive models have appeared, new tangible and intangible resources are being built and new competitive regulations form a new competitive framework which opens the field to new opportunities and new threats. With this dynamic, companies are rushing towards the development of their strategic decision system which must be powerful to follow any material (product and service) or immaterial resource (belief, knowledge, know-how) coming from one of the direct competitors. In this context, a conceptual study is carried out with the objective to analyze the evolution of cognition-based competition using artificial intelligence (AI) technology as a support for strategic decision-making; this is in order to transform the competition into an intelligent mode. The finding is presented in an intelligent approach designed to generate automatic competition rules based on deep learning techniques.