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In this paper, we propose a new algorithm, called ClaSP for mining frequent closed sequential patterns in temporal transaction data. Our algorithm uses several efficient search space pruning methods together with a vertical database layout. Experiments on both synthetic and real datasets show that ClaSP outperforms currently well known state of the art(More)
STUDY OBJECTIVES To examine neural correlates of working memory performance in patients with primary insomnia (PIs) compared with well-matched good sleepers (GSs). DESIGN Twenty-five PIs and 25 GSs underwent functional MRI while performing an N-back working memory task. SETTING VA hospital sleep laboratory and University-based functional imaging center.(More)
In the Intensive Care Unit (ICU) domain, temporal evolution of diseases and patients' contextual information are critical pieces of knowledge that must be considered in the design of a diagnosis task. The uncertainty inherent in the description of temporal information associated to diseases requires a temporal representation and reasoning framework. This(More)
Extended Abstract The design of knowledge-based systems has received special attention from the beginnings of Artificial Intelligence. In particular, the application of model-based systems has obtained important results in the last decades [1]. However, the experience in developing these systems, far from becoming simpler, reveals the complexity on the(More)
The disruption of the circadian system in humans has been associated with the development of chronic illnesses and the worsening of pre-existing pathologies. Therefore, the assessment of human circadian system function under free living conditions using non-invasive techniques needs further research. Traditionally, overt rhythms such as activity and body(More)
OBJECTIVE The aim of this work is to provide a theoretical framework which is sufficiently expressive to describe temporal evolution of diseases, and also to propose a diagnostic process for building explanations of patient's observed temporal evolution based on these disease descriptions. BACKGROUND Model-based diagnosis (MBD) tackles the problem of(More)
Herpetic encephalitis is the most common cause of viral encephalitis in our country. Pathological studies show progressive necrosis and edema in specific territories of the brain. The mortality of herpetic encephalitis was reduced from 70% to 20% with the use of intravenous aciclovir in the first three days of illness. However, almost 50% of patients(More)
Sequential pattern mining algorithms using a vertical representation are the most efficient for mining sequential patterns in dense or long sequences, and have excellent overall performance. The vertical representation allows generating patterns and calculating their supports without performing costly database scans. However, a crucial performance(More)