In search of an appropriate abstraction level for motif annotations

In: Proceedings of the 2012 Workshop on Computational Models of Narrative, (pp. 22-28).

The OhioLINK Digital Media Center Application Profile: A New Tool for Ohio Digital Collections

Contains fulltext : 219863.pdf (Publisher’s version ) (Open Access)OBJECTIVES: Our goal was to report the long-term serial follow-up after transatrial-transpulmonary repair of tetralogy of Fallot (TOF) and to describe the influence of the timing of the repair on outcome. METHODS: We included all patients with TOF who had undergone transatrial-transpulmonary repair between 1970 and 2012. Records were reviewed for patient demographics, operative details and events during the follow-up period (death, pulmonary valve replacement, cardiac reinterventions and hospitalization/intervention for arrhythmias). In patients with elective early primary repair of TOF after 1990, a subanalysis of the optimal timing of TOF repair was performed. RESULTS: A total of 453 patients were included (63% male patients; 65% had transannular patch); 261 patients underwent primary elective repair after 1990. The median age at TOF repair was 0.7 years (25th-75th percentile 0.3-1.3) and decreased from 1.7 to 0.4 years from before 1990 to after 2000, respectively (P < 0.001). The median follow-up duration after TOF repair was 16.8 years (9.6-24.7). Events developed in 182 (40%) patients. In multivariable analysis, early repair of TOF (<6 months) [hazard ratio (HR) 3.06; P < 0.001] and complications after TOF repair (HR 2.18; P = 0.006) were found to be predictive for an event. In a subanalysis of the primary repair of TOF after 1990, the patients (n = 125) with elective early repair (<6 months) experienced significantly worse event-free survival compared to patients who had elective repair later (n = 136). In multivariable analysis, early repair (HR 3.00; P = 0.001) and postoperative complications (HR 2.12; P = 0.010) were associated with events in electively repaired patients with TOF. CONCLUSIONS: Transatrial-transpulmonary repair of TOF before the age of 6 months may be associated with more events during the long-term follow-up period

Echocardiographic findings associated with mortality or transplant in patients with pulmonary arterial hypertension: A systematic review and meta-analysis

Background Identification of patients at risk of deterioration is essential to guide clinical management in pulmonary arterial hype

Discovering the Language of Wine Reviews: A Text Mining Account

It is widely held that smells and flavors are impossible to put into words. In this paper we test this claim by seeking predictive patterns in wine reviews, which ostensibly aim to provide guides to perceptual content. Wine reviews have previously been critiqued as random and meaningless. We collected an English corpus of wine reviews with their structured metadata, and applied machine learning techniques to automatically predict the winetextquotesingles color, grape variety, and country of origin. To train the three supervised classifiers, three different information sources were incorporated: lexical bag-of-words features, domain-specific terminology features, and semantic word embedding features. In addition, using regression analysis we investigated basic review properties, i.e., review length, average word length, and their relationship to the scalar values of price and review score. Our results show that wine experts do share a common vocabulary to describe wines and they use this in a consistent way, which makes it possible to automatically predict wine characteristics based on the review text alone. This means that odors and flavors may be more expressible in language than typically acknowledged

Taal in uitvoering

Contains fulltext : 100882.pdf (publisher's version ) (Open Access)Rede, uitgesproken bij de openbare aanvaarding van het ambt van hoogleraar Example-Based Language Modelling aan de Radboud Universiteit Nijmegen op 9 november 2012, 9 november 201232 p

Effects of context and recency in scaled word completion

Contains fulltext : M_337892.pdf (publisher's version ) (Open Access)The commonly accepted method for fast and e cient word completion is storage and retrieval of character n-grams in tries. We perform learning curve experiments to measure the scaling performance of the trie approach, and present three extensions. First, we extend the trie to store characters of previous words. Second, we extend the trie to the double task of completing the current word and predicting the next word. Third, we augment the trie with a recent word bu er to account for the fact that recently used words have a high chance of recurring. Learning curve experiments on English and Dutch newspaper texts show that (1) storing the characters of previous words yields an increasing and substantial improvement over the baseline with more data, also when compared to a word-based text completion baseline; (2) simultaneously predicting the next word provides an additional small improvement; and (3) the initially large contribution of a recency model diminishes when the trie is trained on more background training data.16 p

Memory-based named entity recognition in tweets

Contains fulltext : 116164.pdf (publisher's version ) (Open Access)We present a memory-based named entity recognition system that participated in the MSM-2013 Concept Extraction Challenge. The system expands the training set of annotated tweets with part-of-speech tags and seedlist information, and then generates a sequential memory-based tagger comprised of separate modules for known and unknown words. Two taggers are trained: one on the original capitalized data, and one on a lowercased version of the training data. The intersection of named entities in the predictions of the two taggers is kept as the final output.Concept Extraction Challenge at Making Sense of Microposts 201

Memory-based text correction for preposition and determiner errors

Contains fulltext : 2101867.pdf (publisher's version ) (Open Access

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Contains fulltext : 101906.pdf (publisher's version ) (Open Access)1 p

Leveraging unscheduled event prediction through mining scheduled event tweets

Contains fulltext : 101833.pdf (author's version ) (Open Access)24th Benelux Conference on Artficial Intelligence, 25 oktober 201