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Frailty is a physiological state characterized by the deregulation of multiple physiologic systems of an aging organism determining the loss of homeostatic capacity, which exposes the elderly to disability, diseases, and finally death. An operative definition of frailty, useful for the classification of the individual quality of aging, is needed. On the(More)
Preservation of functional ability is a well-recognized marker of longevity. At a molecular level, a major determinant of the physiological decline occurring with aging is the imbalance between production and accumulation of oxidative damage to macromolecules, together with a decreased efficiency of stress response to avoid or repair such damage. In this(More)
BACKGROUND AND PURPOSE Residual brain function has been documented in vegetative state patients, yet early prognosis remains difficult. The purpose of this study was to identify by artificial intelligence procedures (classification and regression trees, data-mining) the significant neurological signs correlated to and predictive of outcome. METHODS Three(More)
The European STREP project HEARTFAID aims at defining an innovative platform of services able to intelligently support clinical operators in the daily management of heart failure patients. The core of the platform intelligence is a Clinical Decision Support System, developed by integrating innovative knowledge representation techniques and hybrid reasoning(More)
MOTIVATION Variable selection is a typical approach used for molecular-signature and biomarker discovery; however, its application to survival data is often complicated by censored samples. We propose a new algorithm for variable selection suitable for the analysis of high-dimensional, right-censored data called Survival Max-Min Parents and Children(More)
In a typical supervised data analysis task, one needs to perform the following two tasks: (a) select the best combination of learning methods (e.g., for variable selection and classifier) and tune their hyper-parameters (e.g., K in K-NN), also called model selection, and (b) provide an estimate of the performance of the final, reported model. Combining the(More)
In this paper we address the problem of incorporating prior knowledge, in the form of causal relations, in causal models. Prior approaches mostly consider knowledge about the presence or absence of edges in the model. We use the formalism of Maximal Ancestral Graphs (MAGs) and adapt cSAT+ to solve this problem, an algorithm for reasoning with datasets(More)
We present methods able to predict the presence and strength of conditional and unconditional dependencies (correlations) between two variables Y and Z never jointly measured on the same samples, based on multiple data sets measuring a set of common variables. The algorithms are specializations of prior work on learning causal structures from overlapping(More)
An efficient uncoupling process is generally considered to have a protective effect on the aging muscle by slowing down its age-related decay. Genetic polymorphisms in the Uncoupling Protein 3 (UCP3) gene, whose product is mainly expressed in skeletal muscle, were suggested to be associated with hand grip (HG) performances in elderly populations.(More)