988 resultados para Loss labeling (classification)


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Prostate-specific antigen (PSA) and the related kallikrein family of serine proteases are current or emerging biomarkers for prostate cancer detection and progression. Kallikrein 4 (KLK4/hK4) is of particular interest, as KLK4 mRNA has been shown to be elevated in prostate cancer. In this study, we now show that the comparative expression of hK4 protein in prostate cancer tissues, compared with benign glands, is greater than that of PSA and kallikrein 2 (KLK2/hK2), suggesting that hK4 may play an important functional role in prostate cancer progression in addition to its biomarker potential. To examine the roles that hK4, as well as PSA and hK2, play in processes associated with progression, these kallikreins were separately transfected into the PC-3 prostate cancer cell line, and the consequence of their stable transfection was investigated. PC-3 cells expressing hK4 had a decreased growth rate, but no changes in cell proliferation were observed in the cells expressing PSA or hK2. hK4 and PSA, but not hK2, induced a 2.4-fold and 1.7-fold respective increase, in cellular migration, but not invasion, through Matrigel, a synthetic extracellular matrix. We hypothesised that this increase in motility displayed by the hK4 and PSA-expressing PC-3 cells may be related to the observed change in structure in these cells from a typical rounded epithelial-like cell to a spindle-shaped, more mesenchymal-like cell, with compromised adhesion to the culture surface. Thus, the expression of E-cadherin and vimentin, both associated with an epithelial-mesenchymal transition (EMT), was investigated. E-cadherin protein was lost and mRNA levels were significantly decreased in PC-3 cells expressing hK4 and PSA (10-fold and 7-fold respectively), suggesting transcriptional repression of E-cadherin, while the expression of vimentin was increased in these cells. The loss of E-cadherin and associated increase in vimentin are indicative of EMT and provides compelling evidence that hK4, in particular, and PSA have a functional role in the progression of prostate cancer through their promotion of tumour cell migration.

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Background Definitive cisplatin-based is increasingly delivered as the treatment of choice for patients with head and neck cancer. Sensorineural hearing loss is a significant long term side effect of cisplatin-based chemoradiation and is associated with potential major quality of life issues for patients. Purpose The purpose of this manuscript was to review the mechanism behind sensorineural hearing loss in patients treated with cisplatin-based chemoradiation, including incidence, the contributions of radiotherapy and cisplatin to sensorineural hearing loss and the impact of the toxicity on patient quality of life. Methods Database searches were conducted through PubMed (National Centre for Biotechnology Information) and OvidSP Medline via the Queensland University of Technology Library website. General article searches were conducted through the online search engine Google Scholar. Articles were excluded if the full-text was unavailable, they were not in English or if they were published prior to 1990. Keywords included hearing loss, ototoxicity, cancer, quality of life, cisplatin and radiotherapy. Results/Discussion The total number of journal articles accessed was 290. Due to exclusion criteria, 129 articles were deemed appropriated for review. Findings indicated that sensorineural hearing loss is a significant, long term complication for patients treated with cisplatin-based chemoradiation. Current literature recognises the ototoxic effects of cisplatin and cranial irradiation as separate entities, however the impact of combined modality therapy on sensorineural hearing loss is seldom reported. Multiple risk factors for hearing loss are described, however there are contradictory opinions on incidence and severity and the exact radiation dose threshold responsible for inducing hearing loss in patients receiving combined modality therapy. Sensorineural hearing loss creates a subset of complexities for patients with head and neck cancer and that these patients face significant quality of life impairment. Conclusion The literature review identified that sensorineural hearing loss is a major quality of life issue for patients treated with cisplatin-based chemoradiation for head and neck cancer. Further investigation evaluating the contribution of cisplatin-based chemoradiation to sensorineural hearing loss and the subsequent effect on patient quality of life is warranted.

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This thesis undertakes an empirical investigation to identify factors that influence the decision to undertake weight loss behaviour using the nationally representative HILDA dataset. Although many factors influenced the decision, the findings suggested that body weight satisfaction was the greatest determinant of weight loss dieting. This thesis therefore conducted a further empirical study to analyse the determinants of body weight satisfaction. A rank-hypothesis was found to better predict variation in body weight satisfaction levels than the absolute value of the individual's Body Mass Index (BMI) or the relative-norm hypothesis, which are commonly reported in the literature.

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We present an overview of the QUT plant classification system submitted to LifeCLEF 2014. This system uses generic features extracted from a convolutional neural network previously used to perform general object classification. We examine the effectiveness of these features to perform plant classification when used in combination with an extremely randomised forest. Using this system, with minimal tuning, we obtained relatively good results with a score of 0:249 on the test set of LifeCLEF 2014.

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Aim: To quantify the consequences of major threats to biodiversity, such as climate and land-use change, it is important to use explicit measures of species persistence, such as extinction risk. The extinction risk of metapopulations can be approximated through simple models, providing a regional snapshot of the extinction probability of a species. We evaluated the extinction risk of three species under different climate change scenarios in three different regions of the Mexican cloud forest, a highly fragmented habitat that is particularly vulnerable to climate change. Location: Cloud forests in Mexico. Methods: Using Maxent, we estimated the potential distribution of cloud forest for three different time horizons (2030, 2050 and 2080) and their overlap with protected areas. Then, we calculated the extinction risk of three contrasting vertebrate species for two scenarios: (1) climate change only (all suitable areas of cloud forest through time) and (2) climate and land-use change (only suitable areas within a currently protected area), using an explicit patch-occupancy approximation model and calculating the joint probability of all populations becoming extinct when the number of remaining patches was less than five. Results: Our results show that the extent of environmentally suitable areas for cloud forest in Mexico will sharply decline in the next 70 years. We discovered that if all habitat outside protected areas is transformed, then only species with small area requirements are likely to persist. With habitat loss through climate change only, high dispersal rates are sufficient for persistence, but this requires protection of all remaining cloud forest areas. Main conclusions: Even if high dispersal rates mitigate the extinction risk of species due to climate change, the synergistic impacts of changing climate and land use further threaten the persistence of species with higher area requirements. Our approach for assessing the impacts of threats on biodiversity is particularly useful when there is little time or data for detailed population viability analyses. © 2013 John Wiley & Sons Ltd.

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We consider online prediction problems where the loss between the prediction and the outcome is measured by the squared Euclidean distance and its generalization, the squared Mahalanobis distance. We derive the minimax solutions for the case where the prediction and action spaces are the simplex (this setup is sometimes called the Brier game) and the \ell_2 ball (this setup is related to Gaussian density estimation). We show that in both cases the value of each sub-game is a quadratic function of a simple statistic of the state, with coefficients that can be efficiently computed using an explicit recurrence relation. The resulting deterministic minimax strategy and randomized maximin strategy are linear functions of the statistic.

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Narrative text is a useful way of identifying injury circumstances from the routine emergency department data collections. Automatically classifying narratives based on machine learning techniques is a promising technique, which can consequently reduce the tedious manual classification process. Existing works focus on using Naive Bayes which does not always offer the best performance. This paper proposes the Matrix Factorization approaches along with a learning enhancement process for this task. The results are compared with the performance of various other classification approaches. The impact on the classification results from the parameters setting during the classification of a medical text dataset is discussed. With the selection of right dimension k, Non Negative Matrix Factorization-model method achieves 10 CV accuracy of 0.93.

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This thesis presents a promising boundary setting method for solving challenging issues in text classification to produce an effective text classifier. A classifier must identify boundary between classes optimally. However, after the features are selected, the boundary is still unclear with regard to mixed positive and negative documents. A classifier combination method to boost effectiveness of the classification model is also presented. The experiments carried out in the study demonstrate that the proposed classifier is promising.

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Individuals with limb amputation fitted with conventional socket-suspended prostheses often experience socket related discomfort leading to a significant decrease in quality of life. Most of these concerns can be overcome by surgical techniques enabling bone-anchored prostheses. In this case, the prosthesis is attached directly to the residual skeleton through a percutaneous implant. The aim of this study is to present the current advances in these surgical techniques worldwide with a strong focus on the developments in Australia and Queensland.

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Background There is a need for better understanding of the dispersion of classification-related variable to develop an evidence-based classification of athletes with a disability participating in stationary throwing events. Objectives The purposes of this study are (A) to describe tools designed to comprehend and represent the dispersion of the performance between successive classes, and (B) to present this dispersion for the elite male and female stationary shot-putters who participated in Beijing 2008 Paralympic Games. Study design Retrospective study Methods This study analysed a total of 479 attempts performed by 114 male and female stationary shot-putters in three F30s (F32-F34) and six F50s (F52-F58) classes during the course of eight events during Beijing 2008 Paralympic Games. Results The average differences of best performance were 1.46±0.46 m for males between F54 and F58 classes as well as 1.06±1.18 m for females between F55 and F58 classes. The results demonstrated a linear relationship between best performance and classification while revealing two male Gold Medallists in F33 and F52 classes were outliers. Conclusions This study confirms the benefits of the comparative matrices, performance continuum and dispersion plots to comprehend classification-related variables. The work presented here represents a stepping stone into biomechanical analyses of stationary throwers, particularly on the eve of the London 2012 Paralympic Games where new evidences could be gathered.

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This document has arisen from a request from BM Alliance Coal Operations Pty Ltd, to undertake and report on the key findings and statistics, key learning’s and recommendations for vehicle rollover and loss of traction (skid) incidents that have occurred at various BM Alliance coal operation mines in Queensland.

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Traditional text classification technology based on machine learning and data mining techniques has made a big progress. However, it is still a big problem on how to draw an exact decision boundary between relevant and irrelevant objects in binary classification due to much uncertainty produced in the process of the traditional algorithms. The proposed model CTTC (Centroid Training for Text Classification) aims to build an uncertainty boundary to absorb as many indeterminate objects as possible so as to elevate the certainty of the relevant and irrelevant groups through the centroid clustering and training process. The clustering starts from the two training subsets labelled as relevant or irrelevant respectively to create two principal centroid vectors by which all the training samples are further separated into three groups: POS, NEG and BND, with all the indeterminate objects absorbed into the uncertain decision boundary BND. Two pairs of centroid vectors are proposed to be trained and optimized through the subsequent iterative multi-learning process, all of which are proposed to collaboratively help predict the polarities of the incoming objects thereafter. For the assessment of the proposed model, F1 and Accuracy have been chosen as the key evaluation measures. We stress the F1 measure because it can display the overall performance improvement of the final classifier better than Accuracy. A large number of experiments have been completed using the proposed model on the Reuters Corpus Volume 1 (RCV1) which is important standard dataset in the field. The experiment results show that the proposed model has significantly improved the binary text classification performance in both F1 and Accuracy compared with three other influential baseline models.

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Affect is an important feature of multimedia content and conveys valuable information for multimedia indexing and retrieval. Most existing studies for affective content analysis are limited to low-level features or mid-level representations, and are generally criticized for their incapacity to address the gap between low-level features and high-level human affective perception. The facial expressions of subjects in images carry important semantic information that can substantially influence human affective perception, but have been seldom investigated for affective classification of facial images towards practical applications. This paper presents an automatic image emotion detector (IED) for affective classification of practical (or non-laboratory) data using facial expressions, where a lot of “real-world” challenges are present, including pose, illumination, and size variations etc. The proposed method is novel, with its framework designed specifically to overcome these challenges using multi-view versions of face and fiducial point detectors, and a combination of point-based texture and geometry. Performance comparisons of several key parameters of relevant algorithms are conducted to explore the optimum parameters for high accuracy and fast computation speed. A comprehensive set of experiments with existing and new datasets, shows that the method is effective despite pose variations, fast, and appropriate for large-scale data, and as accurate as the method with state-of-the-art performance on laboratory-based data. The proposed method was also applied to affective classification of images from the British Broadcast Corporation (BBC) in a task typical for a practical application providing some valuable insights.

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Directly after the horrific events of September 11, 2001, many Americans were saying the same thing: the world has changed forever. They were overwhelmed with a sense that “the party was over.” It was clear that America had lost its innocence; it now had to “grow up.” Much of the fiction produced since 9/11 and with 9/11 at its core provides evidence of the larger cultural belief that September 11 was a turning point (much like adolescence) from which there is no turning back. In this chapter, I examine how three post-9/11 novels—Lorrie Moore’s A Gate at the Stairs, Joyce Maynard’s The Usual Rules, and John Updike’s Terrorist—position readers to understand September 11 as a moment that changed how young Americans come of age.

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Ghrelin and leptin are key peripherally secreted appetite-regulating hormones in vertebrates. Here we consider the ghrelin gene (GHRL) of birds (class Aves), where it has been reported that ghrelin inhibits rather than augments feeding. Thirty-one bird species were compared, revealing that most species harbour a functional copy of GHRL and the coding region for its derived peptides ghrelin and obestatin. We provide evidence for loss of GHRL in saker and peregrine falcons, and this is likely to result from the insertion of an ERVK retrotransposon in intron 0. We hypothesise that the loss of anorexigenic ghrelin is a predatory adaptation that results in increased food-seeking behaviour and feeding in falcons.