Cardiovascular Attributable Risk and Risk Factors Evaluations as a Matter of Statistics and Data Mining Confluences

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.Cardiovascular Disease, Myocardial Infarction, Attributable Risk, Roc, Data Mining, Classification

Preprocessing and Content/Navigational Pages Identification as Premises for an Extended Web Usage Mining Model Development

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.Knowledge Management, Web Mining, Data Preprocessing, Decision Trees, Databases

Initiatives in the Romanian eHealth Landscape

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

An Integrated Solution for Pavement Management and Monitoring Systems

AbstractThe aim of this paper is to present a holistic platform for pavement monitoring and maintenance management (PMMP). Our solution tries to exploit new technologies in order to design, integrate and implement an automated and portable visual road inspection system for traffic-speed pavement distress monitoring and analysis that can be installed on non-specialized vehicles. PAV3M developed based on solution based on PMMS requirements and recommendation made in EU programs as a modular decomposition based on business process analysis. For road monitoring and maintenance we opted for LCCA methods. Our solution includes Risk management module

Smart homes for older people involved in rehabilitation activities - reality or dream, acceptance or rejection?

Introduction Recent statistics show an increase in the prevalence of the elderly population. The year 2012 was declared European Year for Active Ageing and Solidarity between Generations, and the European Commission launched campaigns like The Active and Assisted Living Joint Program (AAL JP). Rehabilitation in the elderly is a desideratum, but the problems of rehabilitation in the elderly are numerous. The aim of the study was to evaluate degree of acceptance/implementation of different technologies in Romania, of monitoring in the rehabilitation activity conducted at home. Material and methods the study comprised 154 persons with a mean age of 73.37 ± 7.33 years, of which 64 (41.6%) male and 90 (58.4%) female. All subjects completed a questionnaire regarding the living conditions and health status, about the degree of acceptance of intelligent technologies for monitoring current health status/reporting acute events. Results 18.2% used the Internet frequently, and the rest used it almost never or rarely. 71.9 % of patients agreed to wear a portable sensor (p=0.07 between men and women), 33.1% accepted videocam, 47.4% accepted a screen, 41.3% accepted living room monitoring, 68% sensor in the room on the wall and 69.1% accepted fall detection sensor. No significant differences were found regarding the acceptance vs rejection of personal sensors, living room monitoring, sensors in the room, fall detection sensors depending on the gender, income level, type of caregiving. Using of videocam and screen was influenced by type of care giving and income (p=0.002, p<0.001, respectively for screen p=0.032 and p=0.003). In conclusion, Romanian old people are not keen on using intelligent devices for health status related to acute event monitoring. More programs and measures are needed for device implementation in real life

Cardiac Toxicity Associated with Immune Checkpoint Inhibitors: A Systematic Review

Immune checkpoint inhibitors (ICIs) are an important advancement in the field of cancer treatment, significantly improving the survival of patients with a series of advanced malignancies, like melanoma, non-small cell lung cancer (NSCLC), hepatocellular carcinoma (HCC), renal cell carcinoma (RCC), and Hodgkin lymphoma. ICIs act upon T lymphocytes and antigen-presenting cells, targeting programmed cell death protein 1 (PD1), programmed cell death protein ligand 1 (PD-L1), and cytotoxic T-lymphocyte antigen 4 (CTLA-4), breaking the immune tolerance of the T cells against malignant cells and enhancing the body’s own immune response. A variety of cardiac-adverse effects are associated with ICI-based treatment, including pericarditis, arrhythmias, cardiomyopathy, and acute coronary syndrome, with myocarditis being the most studied due to its often-unexpected onset and severity. Overall, Myocarditis is rare but presents an immune-related adverse event (irAE) that has a high fatality rate. Considering the rising number of oncological patients treated with ICIs and the severity of their potential adverse effects, a good understanding and continuous investigation of cardiac irAEs is of the utmost importance. This systematic review aimed to revise recent publications (between 2016–2022) on ICI-induced cardiac toxicities and highlight the therapeutical approach and evolution in the selected cases