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Search Results: 1 - 7 of 7 matches for " Socher "
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Avalia??o da qualidade de vida de pacientes com vertigem posicional paroxística benigna associada à doen?a de Ménière pré e pós reabilita??o vestibular
Socher, Dayra Dill;Socher, Jan Alessandro;Azzi, Viviane Jacintha Bolfe;
International Archives of Otorhinolaryngology , 2012, DOI: 10.7162/S1809-97772012000400002
Abstract: introduction: vertigo is a symptom that impacts the patients' quality of life and may force them to cease performing activities of daily living. here, we discuss benign paroxysmal positional vertigo (bppv) and meniere's disease (md), which show exacerbated symptoms when they appear in association. vestibular rehabilitation (vr) is an effective treatment in reducing vertigo, especially in conjunction with other therapies. aim: to evaluate the quality of life of patients with bppv and md before and after vr. method: we conducted a descriptive observational qualitative and quantitative case study with 12 patients aged 35 to 86 years. all patients diagnosed with bppv and md received treatment in the ent clinic. the brazilian dhi questionnaire, which assesses the quality of life with a focus on physical, emotional, and functional aspects, was used for data collection, and was completed by patients before the first session and after the fifth session of vr. data were tested using the shapiro-wilk normality test, followed by wilcoxon, friedman, and spearman correlation tests (p < 0.05). results: there were significant improvements in scores for all aspects, with median changes ranging from 12 to 0 in the physical, 6 to 1 in the emotional, and 11 to 1 in the functional aspect. there were no correlations between the scores and sample characteristics. conclusion: vr was an effective method for the treatment of patients with bppv and md; it improves quality of life and shows the maximal influence on physical aspect scores, regardless of age or gender.
Evaluation of quality of life pre- and post-vestibular rehabilitation in patients with benign paroxysmal positional vertigo associated with Meniere's disease
Socher, Dayra Dill,Socher, Jan Alessandro,Azzi, Viviane Jacintha Bolfe
International Archives of Otorhinolaryngology , 2012,
Abstract: Introduction: Vertigo is a symptom that impacts the patients' quality of life and may force them to cease performing activities of daily living. Here, we discuss benign paroxysmal positional vertigo (BPPV) and Meniere's disease (MD), which show exacerbated symptoms when they appear in association. Vestibular rehabilitation (VR) is an effective treatment in reducing vertigo, especially in conjunction with other therapies. Aim: To evaluate the quality of life of patients with BPPV and MD before and after VR. Method: We conducted a descriptive observational qualitative and quantitative case study with 12 patients aged 35 to 86 years. All patients diagnosed with BPPV and MD received treatment in the ENT clinic. The Brazilian DHI questionnaire, which assesses the quality of life with a focus on physical, emotional, and functional aspects, was used for data collection, and was completed by patients before the first session and after the fifth session of VR. Data were tested using the Shapiro-Wilk normality test, followed by Wilcoxon, Friedman, and Spearman correlation tests (p < 0.05). Results: There were significant improvements in scores for all aspects, with median changes ranging from 12 to 0 in the physical, 6 to 1 in the emotional, and 11 to 1 in the functional aspect. There were no correlations between the scores and sample characteristics. Conclusion: VR was an effective method for the treatment of patients with BPPV and MD; it improves quality of life and shows the maximal influence on physical aspect scores, regardless of age or gender.
Learning New Facts From Knowledge Bases With Neural Tensor Networks and Semantic Word Vectors
Danqi Chen,Richard Socher,Christopher D. Manning,Andrew Y. Ng
Computer Science , 2013,
Abstract: Knowledge bases provide applications with the benefit of easily accessible, systematic relational knowledge but often suffer in practice from their incompleteness and lack of knowledge of new entities and relations. Much work has focused on building or extending them by finding patterns in large unannotated text corpora. In contrast, here we mainly aim to complete a knowledge base by predicting additional true relationships between entities, based on generalizations that can be discerned in the given knowledgebase. We introduce a neural tensor network (NTN) model which predicts new relationship entries that can be added to the database. This model can be improved by initializing entity representations with word vectors learned in an unsupervised fashion from text, and when doing this, existing relations can even be queried for entities that were not present in the database. Our model generalizes and outperforms existing models for this problem, and can classify unseen relationships in WordNet with an accuracy of 75.8%.
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
Kai Sheng Tai,Richard Socher,Christopher D. Manning
Computer Science , 2015,
Abstract: Because of their superior ability to preserve sequence information over time, Long Short-Term Memory (LSTM) networks, a type of recurrent neural network with a more complex computational unit, have obtained strong results on a variety of sequence modeling tasks. The only underlying LSTM structure that has been explored so far is a linear chain. However, natural language exhibits syntactic properties that would naturally combine words to phrases. We introduce the Tree-LSTM, a generalization of LSTMs to tree-structured network topologies. Tree-LSTMs outperform all existing systems and strong LSTM baselines on two tasks: predicting the semantic relatedness of two sentences (SemEval 2014, Task 1) and sentiment classification (Stanford Sentiment Treebank).
O cidad o nas políticas públicas: realidade ou utopia? The citizen in public policy: reality or utopia?
Paulo Roberto Socher,Osmar Ponchirolli,Jose Edmilson de Souza-Lima,Sandra Mara Maciel-Lima
Urbe : Revista Brasileira de Gest?o Urbana , 2010,
Abstract: O artigo se prop e a identificar elementos contributivos que levem as políticas públicas a reconsiderar o cidad o como ator principal da esfera pública, verificando evidências de sua utiliza o em linhas estratégicas municipais. A partir da discuss o teórica do papel do cidad o, fundamentada na Teoria da Complexidade, e posterior aproveitamento de modelos atuais de linhas estratégicas de cidades referência para fins de comparabilidade, foi possível fundamentar e apresentar resultados de forma a responder qual papel tem sido destinado ao cidad o nas declara es de inten es dos gestores municipais, bem como sob quais influências de modelos epistemológicos e de desenvolvimento se encontram tais políticas públicas. Por meio de pesquisa qualitativa e exploratória, conclui-se que na maioria das experiências de políticas públicas analisadas, o cidad o, quando é levado em considera o, ocupa posi es secundárias. Do ponto de vista teórico, isso se deve ao fato de predominarem nos processos de elabora o das políticas públicas racionalidades lineares, instrumentais e excludentes, em detrimento de racionalidades n o lineares e abertas aos anseios dos cidad os.
Zero-Shot Learning Through Cross-Modal Transfer
Richard Socher,Milind Ganjoo,Hamsa Sridhar,Osbert Bastani,Christopher D. Manning,Andrew Y. Ng
Computer Science , 2013,
Abstract: This work introduces a model that can recognize objects in images even if no training data is available for the objects. The only necessary knowledge about the unseen categories comes from unsupervised large text corpora. In our zero-shot framework distributional information in language can be seen as spanning a semantic basis for understanding what objects look like. Most previous zero-shot learning models can only differentiate between unseen classes. In contrast, our model can both obtain state of the art performance on classes that have thousands of training images and obtain reasonable performance on unseen classes. This is achieved by first using outlier detection in the semantic space and then two separate recognition models. Furthermore, our model does not require any manually defined semantic features for either words or images.
Ask Me Anything: Dynamic Memory Networks for Natural Language Processing
Ankit Kumar,Ozan Irsoy,Peter Ondruska,Mohit Iyyer,James Bradbury,Ishaan Gulrajani,Richard Socher
Computer Science , 2015,
Abstract: Most tasks in natural language processing can be cast into question answering (QA) problems over language input. We introduce the dynamic memory network (DMN), a unified neural network framework which processes input sequences and questions, forms semantic and episodic memories, and generates relevant answers. Questions trigger an iterative attention process which allows the model to condition its attention on the result of previous iterations. These results are then reasoned over in a hierarchical recurrent sequence model to generate answers. The DMN can be trained end-to-end and obtains state of the art results on several types of tasks and datasets: question answering (Facebook's bAbI dataset), sequence modeling for part of speech tagging (WSJ-PTB), coreference resolution (Quizbowl dataset) and text classification for sentiment analysis (Stanford Sentiment Treebank). The model relies exclusively on trained word vector representations and requires no string matching or manually engineered features.
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