In this paper, we first argue that various ways of using context in WSD can be considered as distinct representations of a polysemous word under consideration, then all these representations are used jointly to identify the meaning of the target word. Under such a consideration, we can then straightforwardly apply the general framework for combining classifiers developed in Kittler et al. [5] t...

In the first half of the 20th century, the polio pandemic spread across much of the world, afflicting hundreds of thousands each year. Mounting a response to this global health crisis required consensus, common language, and dedication among lawmakers, philanthropists , industrialists, patient advocates , and healthcare providers. A diverse group from many industries, both public and private, c...

Background Neonatal sepsis is one of the major causes of neonatal morbidity and mortality globally. Its incidence varies from 1 to 4 cases per 1,000 live births in developed countries. The burden of the problem occurs in the developing world while most confirmation is derived from developed countries. This study is aimed to assess the prevalence of neonatal sepsi...

Word sense disambiguation (WSD) and coreference resolution are two fundamental tasks for natural language processing. Unfortunately, they are seldom studied together. In this paper, we propose to incorporate the coreference resolution technique into a word sense disambiguation system for improving disambiguation precision. Our work is based on the existing instance knowledge network (IKN) based...

Although it has been always thought that Word Sense Disambiguation (WSD) can be useful for Machine Translation, only recently efforts have been made towards integrating both tasks to prove that this assumption is valid, particularly for Statistical Machine Translation (SMT). While different approaches have been proposed and results started to converge in a positive way, it is not clear yet how ...

This paper describes our word sense disambiguation (WSD) system participating in the SemEval-2007 tasks. The core system is a fully supervised system based on a Naïve Bayes classifier using multiple knowledge sources. Toward a larger goal of incorporating the intrinsic nature of individual target words in disambiguation, thus introducing a cognitive element in automatic WSD, we tried to fine-tu...

Word Sense Disambiguation (WSD) is one of the toughest problems in NLP, and in WSD, verb disambiguation has proved to be extremely difficult, because of high degree of polysemy, too fine grained senses, absence of deep verb hierarchy and low inter annotator agreement in verb sense annotation. Unsupervised WSD has received widespread attention, but has performed poorly, specially on verbs. Recen...

Severe sepsis remains the leading cause of mortality in the critically ill. Local epidemiological studies on sepsis are of paramount importance to increase our knowledge about sepsis features and to improve patient care and prognosis.Adult patients (≥20 years) admitted to the surgical intensive care units with severe sepsis or septic shock from 2009 to 2010 were retrospectively retrieved and an...

BACKGROUND Recognizing infection is crucial in immunocompromised patients with organ dysfunction. Our objective was to assess the diagnostic accuracy of procalcitonin (PCT) in critically ill immunocompromised patients. METHODS This prospective, observational study included patients with suspected sepsis. Patients were classified into one of three diagnostic groups: no infection, bacterial sep...

abstract objective: to assess the incidence of thrombocytopenia and changes in various platelet parameters, in culture positive neonatal sepsis. methods: this was prospective study conducted over a period of one year from december 2009 to november 2010 in neonatal intensive care unit of dduh hospital, a tertiary care hospital in delhi, north india. all babies who were admitted during this perio...