A multidisciplinary team assessed 23 patients with various manifestations of the Noonan syndrome, including pulmonary valve stenosis (with leaflet dysplasia), "typical" facial appearance (including hypertelorism, epicanthic folds, flat nasal bridge, and apparently low-set ears), short stature, and mental retardation. Seven patients had a family history of the syndrome. A comprehensive scoring system was devised on the basis of frequency and severity of manifestations and results of invasive and noninvasive tests in these patients and those reported in the literature. The scoring system was condensed into a score card for clinical use and validated by "blind" application to patients with isolated pulmonary valve stenosis or suspected Noonan syndrome. Use of a scoring system to diagnose a syndrome for which there is no specific diagnostic test facilitates accuracy and decreases observer bias. In the case of unusual congenital disorders it is particularly valuable for a pediatrician in general practice.

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Abstract. Recent work in sentiment analysis has begun to apply finegrained semantic distinctions between expressions of attitude as features for textual analysis. Such methods, however, require the construction of large and complex lexicons, giving values for multiple sentiment-related attributes to many different lexical items. For example, a key attribute is what type of attitude is expressed by a lexical item; e.g., beautiful expresses appreciation of an object's quality, while evil expresses a negative judgment of social behavior. In this chapter we describe a method for the automatic determination of complex sentiment-related attributes such as attitude type and force, by applying supervised learning to WordNet glosses. Experimental results show that the method achieves good effectiveness, and is therefore well-suited to contexts in which these lexicons need to be generated from scratch.

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