Mining transaction databases for association rules usually generates a large number of rules, most of which are unnecessary when used for subsequent prediction. In this paper we define a rule set for a given transaction database that is much smaller than the association rule set but makes the same predictions as the association rule set by the confidence priority. We call this subset the inform...

We read with interest the recently published paper by Hilder et al. [1], where the authors present the PRESET-Score, a new clinical prediction rule for patients with acute respiratory distress syndrome treated with extracorporeal membrane oxygenation (ECMO). While the topic is clinically relevant and interesting, we are worried that spurious findings, biased results, and overstated findings are...

This paper places the perception of noise annoyance within the framework of environmental assessment. It is shown that due to the inherent vagueness and uncertainties in the involved concepts, available data and knowledge, fuzzy techniques are very well suited for the modeling of this perception. This idea is then used to construct a fuzzy rule based model for the prediction of the level of gen...

All radiation therapy treatment planning relies on accurate dose calculation. Uncertainties in dosimetric prediction can significantly degrade an otherwise optimal plan. In this work, we introduce a robust optimization method which handles dosimetric errors and warrants for high-quality IMRT plans. Unlike other dose error estimations, we do not rely on the detailed knowledge about the sources o...

Efforts to anticipate threats to biodiversity take the form of species richness predictions (SRPs) based on simple correlations with current climate and habitat area. We review the major approaches that have been used for SRP, species-area curves and climate envelopes, and suggest that alternative research efforts may provide more understanding and guidance for management. Extinction prediction...

A new method for assessing the similarity of crystal structures is described. A similarity measure is important in classification and clustering problems in which the crystal structures are the source of information. Classification is particularly important for the understanding of properties of crystals, while clustering can be used as a data reduction step in polymorph prediction. The method ...

Extensive evidence documents emotional modulation of hippocampus-dependent declarative memory in humans. However, little is known about the emotional modulation of striatum-dependent procedural memory. To address how emotional arousal influences declarative and procedural memory, the current study utilized (1) a picture recognition and (2) a weather prediction (WP) task (a probabilistic classif...

BACKGROUND Homology modeling is an important technique for making use of the rapidly increasing number of protein sequences in the absence of structural information. The major problems in such modeling, once the alignment has been made, concern the positions of loops and the orientations of sidechains. Although progress has been made in recent years for sidechain prediction, current methods app...

In the heavy quark limit inclusive production rate of a heavy meson can be factorized, in which the nonperturbative effect related to the heavy meson can be characterized by matrix elements defined in the heavy quark effective theory. Using this factorization, predictions for the full spin density matrix of a spin-1 and spin-2 meson can be obtained and they are characterized only by one coeffic...

BACKGROUND Surgical site infection (SSI) surveillance is a key factor in the elaboration of strategies to reduce SSI occurrence and in providing surgeons with appropriate data feedback (risk indicators, clinical prediction rule). AIM To improve the predictive performance of an individual-based SSI risk model by considering a multilevel hierarchical structure. PATIENTS AND METHODS Data were ...