The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Objective: We propose an intelligent system that assists epidemiology experts in analysing the data of a population-based epidemiological study, in identifying relevant variables for an outcome and subpopulations with increased disease prevalence, and in validating the findings concerning variables and subpopulations in a further, expert-specified cohort. At present, the study of an outcome on a population-based...
The identification of predictive features associated with distinct medical outcomes is a key requirement for meaningful clinical decision support. Usually, their discovery is based on sets of labeled examples and an analysis of the inherent information of the features w. r. t. the target variable. However, obtaining large sets of labeled examples may be not feasible and the sole label consideration...
Medical research can greatly benefit from advances in data mining. We propose a mining approach for cohort analysis in a longitudinal population-based epidemiological study, and show that modelling and exploiting the evolution of cohort participants over time improves classification quality towards an outcome (a disease). Our mining workflow encompasses steps for tracing the evolution of the cohort...
Clinical decision support relies on the findings of epidemiological (longitudinal and cross-sectional) studies on predictive features and risk factors for diseases. Such features flow into the diagnostic procedures. Personalized medicine, which aims to optimize clinical decision making by taking individual characteristics of the patients into account, relies on the findings of epidemiology on groups...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.