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Even if the foundation in the field of eHealth was set almost half century ago, the current achievements’ status does not place Romania on a good position in a European ranking. The efforts made during the last years are promising, but they still cannot surpass the enormous gaps in many eHealth indicators. This is not a surprising fact because the eHealth level must be sustained by a healthy and stable sanitary system and infrastructure, which, in our country, is almost in collapse, especially now in the context of global economic and financial crisis. We consider being guilty for these circumstances the lack of a clear and solid mid-term strategy developed at the level of the Ministry of Health (MoH), harmonized in a global legal and regulatory framework as well, and also the non-correlated researcher groups interests. The good attitude of practitioners regarding the challenges of new technologies and the political will can still give a chance to the Romanian healthcare system and to its modern faces.

Cardiovascular diseases represent a severe threat for humanity, being the first cause of death and hospitalization in both genders. An impressive number of studies have been developed in order to identify a set of factors causing this kind of illness, but only few of them were able to pay significant resources in analyzing large population samples (tens of thousands) and for longer periods of time (decades). This paper’s objective is to continue the previous researches of the eProCord project and to validate with concrete data the theoretical model developed for the attributable risk (AR). It will consider the same risk factors for myocardial infarction identified by INTERHEART study and the same work hypothesis. We will also evaluate if a certain value of the AR is also confirmed by the invoked disease of the patient. Using statistical and data mining tools we will investigate the prediction potential of the chosen factors and the opportunity to extend them in order to capture any cardiovascular disease. The empirical tests rely for now on a sample of 236 patients.

From its appearance until nowadays, the internet saw a spectacular growth not only in terms of websites number and information volume, but also in terms of the number of visitors. Therefore, the need of an overall analysis regarding both the web sites and the content provided by them was required. Thus, a new branch of research was developed, namely web mining, that aims to discover useful information and knowledge, based not only on the analysis of websites and content, but also on the way in which the users interact with them. The aim of the present paper is to design a database that captures only the relevant data from logs in a way that will allow to store and manage large sets of temporal data with common tools in real time. In our work, we rely on different web sites or website sections with known architecture and we test several hypotheses from the literature in order to extend the framework to sites with unknown or chaotic structure, which are non-transparent in determining the type of visited pages. In doing this, we will start from non-proprietary, preexisting raw server logs.

Even if the foundation in the field of eHealth was set almost half century ago, the current achievements' status does not place Romania on a good position in a European ranking. The efforts made during the last years are promising, but they still cannot surpass the enormous gaps in many eHealth indicators. This is not a surprising fact because the eHealth level must be sustained by a healthy and stable sanitary system and infrastructure, which, in our country, is almost in collapse, especially now in the context of global economic and financial crisis. We consider being guilty for these circumstances the lack of a clear and solid mid-term strategy developed at the level of the Ministry of Health (MoH), harmonized in a global legal and regulatory framework as well, and also the non-correlated researcher groups interests. The good attitude of practitioners regarding the challenges of new technologies and the political will can still give a chance to the Romanian healthcare system and to its modern faces. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases represent a severe threat for humanity, being the first cause of death and hospitalization in both genders. An impressive number of studies have been developed in order to identify a set of factors causing this kind of illness, but only few of them were able to pay significant resources in analyzing large population samples (tens of thousands) and for longer periods of time (decades). This paper's objective is to continue the previous researches of the eProCord project and to validate with concrete data the theoretical model developed for the attributable risk (AR). It will consider the same risk factors for myocardial infarction identified by INTERHEART study and the same work hypothesis. We will also evaluate if a certain value of the AR is also confirmed by the invoked disease of the patient. Using statistical and data mining tools we will investigate the prediction potential of the chosen factors and the opportunity to extend them in order to capture any cardiovascular disease. The empirical tests rely for now on a sample of 236 patients. [ABSTRACT FROM AUTHOR]

From its appearance until nowadays, the internet saw a spectacular growth not only in terms of websites number and information volume, but also in terms of the number of visitors. Therefore, the need of an overall analysis regarding both the web sites and the content provided by them was required. Thus, a new branch of research was developed, namely web mining, that aims to discover useful information and knowledge, based not only on the analysis of websites and content, but also on the way in which the users interact with them. The aim of the present paper is to design a database that captures only the relevant data from logs in a way that will allow to store and manage large sets of temporal data with common tools in real time. In our work, we rely on different web sites or website sections with known architecture and we test several hypotheses from the literature in order to extend the framework to sites with unknown or chaotic structure, which are non-transparent in determining the type of visited pages. In doing this, we will start from non-proprietary, preexisting raw server logs. [ABSTRACT FROM AUTHOR]