2,955 research outputs found

    Using mammographic density to predict breast cancer risk: dense area or percentage dense area.

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    INTRODUCTION: Mammographic density (MD) is one of the strongest risk factors for breast cancer. It is not clear whether this association is best expressed in terms of absolute dense area or percentage dense area (PDA). METHODS: We measured MD, including nondense area (here a surrogate for weight), in the mediolateral oblique (MLO) mammogram using a computer-assisted thresholding technique for 634 cases and 1,880 age-matched controls from the Cambridge and Norwich Breast Screening programs. Conditional logistic regression was used to estimate the risk of breast cancer, and fits of the models were compared using likelihood ratio tests and the Bayesian information criteria (BIC). All P values were two-sided. RESULTS: Square-root dense area was the best single predictor (for example, χ₁² = 53.2 versus 44.4 for PDA). Addition of PDA and/or square-root nondense area did not improve the fit (both P > 0.3). Addition of nondense area improved the fit of the model with PDA (χ₁² = 11.6; P < 0.001). According to the BIC, the PDA and nondense area model did not provide a better fit than the dense area alone model. The fitted values of the two models were highly correlated (r = 0.97). When a measure of body size is included with PDA, the predicted risk is almost identical to that from fitting dense area alone. CONCLUSIONS: As a single parameter, dense area provides more information than PDA on breast cancer risk

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    Background risk of breast cancer and the association between physical activity and mammographic density

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    This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/ by/4.0

    The prognosis of allocentric and egocentric neglect : evidence from clinical scans

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    We contrasted the neuroanatomical substrates of sub-acute and chronic visuospatial deficits associated with different aspects of unilateral neglect using computed tomography scans acquired as part of routine clinical diagnosis. Voxel-wise statistical analyses were conducted on a group of 160 stroke patients scanned at a sub-acute stage. Lesion-deficit relationships were assessed across the whole brain, separately for grey and white matter. We assessed lesions that were associated with behavioural performance (i) at a sub-acute stage (within 3 months of the stroke) and (ii) at a chronic stage (after 9 months post stroke). Allocentric and egocentric neglect symptoms at the sub-acute stage were associated with lesions to dissociated regions within the frontal lobe, amongst other regions. However the frontal lesions were not associated with neglect at the chronic stage. On the other hand, lesions in the angular gyrus were associated with persistent allocentric neglect. In contrast, lesions within the superior temporal gyrus extending into the supramarginal gyrus, as well as lesions within the basal ganglia and insula, were associated with persistent egocentric neglect. Damage within the temporo-parietal junction was associated with both types of neglect at the sub-acute stage and 9 months later. Furthermore, white matter disconnections resulting from damage along the superior longitudinal fasciculus were associated with both types of neglect and critically related to both sub-acute and chronic deficits. Finally, there was a significant difference in the lesion volume between patients who recovered from neglect and patients with chronic deficits. The findings presented provide evidence that (i) the lesion location and lesion size can be used to successfully predict the outcome of neglect based on clinical CT scans, (ii) lesion location alone can serve as a critical predictor for persistent neglect symptoms, (iii) wide spread lesions are associated with neglect symptoms at the sub-acute stage but only some of these are critical for predicting whether neglect will become a chronic disorder and (iv) the severity of behavioural symptoms can be a useful predictor of recovery in the absence of neuroimaging findings on clinical scans. We discuss the implications for understanding the symptoms of the neglect syndrome, the recovery of function and the use of clinical scans to predict outcome

    SentiBench - a benchmark comparison of state-of-the-practice sentiment analysis methods

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    In the last few years thousands of scientific papers have investigated sentiment analysis, several startups that measure opinions on real data have emerged and a number of innovative products related to this theme have been developed. There are multiple methods for measuring sentiments, including lexical-based and supervised machine learning methods. Despite the vast interest on the theme and wide popularity of some methods, it is unclear which one is better for identifying the polarity (i.e., positive or negative) of a message. Accordingly, there is a strong need to conduct a thorough apple-to-apple comparison of sentiment analysis methods, \textit{as they are used in practice}, across multiple datasets originated from different data sources. Such a comparison is key for understanding the potential limitations, advantages, and disadvantages of popular methods. This article aims at filling this gap by presenting a benchmark comparison of twenty-four popular sentiment analysis methods (which we call the state-of-the-practice methods). Our evaluation is based on a benchmark of eighteen labeled datasets, covering messages posted on social networks, movie and product reviews, as well as opinions and comments in news articles. Our results highlight the extent to which the prediction performance of these methods varies considerably across datasets. Aiming at boosting the development of this research area, we open the methods' codes and datasets used in this article, deploying them in a benchmark system, which provides an open API for accessing and comparing sentence-level sentiment analysis methods

    The epidemiology of injuries across the weight-training sports

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    Background: Weight-training sports, including weightlifting, powerlifting, bodybuilding, strongman, Highland Games, and CrossFit, are weight-training sports that have separate divisions for males and females of a variety of ages, competitive standards, and bodyweight classes. These sports may be considered dangerous because of the heavy loads commonly used in training and competition. Objectives: Our objective was to systematically review the injury epidemiology of these weight-training sports, and, where possible, gain some insight into whether this may be affected by age, sex, competitive standard, and bodyweight class. Methods: We performed an electronic search using PubMed, SPORTDiscus, CINAHL, and Embase for injury epidemiology studies involving competitive athletes in these weight-training sports. Eligible studies included peer-reviewed journal articles only, with no limit placed on date or language of publication. We assessed the risk of bias in all studies using an adaption of the musculoskeletal injury review method. Results: Only five of the 20 eligible studies had a risk of bias score ≥75 %, meaning the risk of bias in these five studies was considered low. While 14 of the studies had sample sizes >100 participants, only four studies utilized a prospective design. Bodybuilding had the lowest injury rates (0.12–0.7 injuries per lifter per year; 0.24–1 injury per 1000 h), with strongman (4.5–6.1 injuries per 1000 h) and Highland Games (7.5 injuries per 1000 h) reporting the highest rates. The shoulder, lower back, knee, elbow, and wrist/hand were generally the most commonly injured anatomical locations; strains, tendinitis, and sprains were the most common injury type. Very few significant differences in any of the injury outcomes were observed as a function of age, sex, competitive standard, or bodyweight class. Conclusion: While the majority of the research we reviewed utilized retrospective designs, the weight-training sports appear to have relatively low rates of injury compared with common team sports. Future weight-training sport injury epidemiology research needs to be improved, particularly in terms of the use of prospective designs, diagnosis of injury, and changes in risk exposure

    The impact of Stieltjes' work on continued fractions and orthogonal polynomials

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    Stieltjes' work on continued fractions and the orthogonal polynomials related to continued fraction expansions is summarized and an attempt is made to describe the influence of Stieltjes' ideas and work in research done after his death, with an emphasis on the theory of orthogonal polynomials
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