55 resultados para Receiver operating characteristic curve

em Cambridge University Engineering Department Publications Database


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We present a systematic, practical approach to developing risk prediction systems, suitable for use with large databases of medical information. An important part of this approach is a novel feature selection algorithm which uses the area under the receiver operating characteristic (ROC) curve to measure the expected discriminative power of different sets of predictor variables. We describe this algorithm and use it to select variables to predict risk of a specific adverse pregnancy outcome: failure to progress in labour. Neural network, logistic regression and hierarchical Bayesian risk prediction models are constructed, all of which achieve close to the limit of performance attainable on this prediction task. We show that better prediction performance requires more discriminative clinical information rather than improved modelling techniques. It is also shown that better diagnostic criteria in clinical records would greatly assist the development of systems to predict risk in pregnancy.

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AIMS: To compare the performance of ultrasound elastography with conventional ultrasound in the assessment of axillary lymph nodes in suspected breast cancer and whether ultrasound elastography as an adjunct to conventional ultrasound can increase the sensitivity of conventional ultrasound used alone. MATERIALS AND METHODS: Fifty symptomatic women with a sonographic suspicion for breast cancer underwent ultrasound elastography of the ipsilateral axilla concurrent with conventional ultrasound being performed as part of triple assessment. Elastograms were visually scored, strain measurements calculated and node area and perimeter measurements taken. Theoretical biopsy cut points were selected. The sensitivity, specificity, positive predictive value (PPV), and negative predictive values (NPV) were calculated and receiver operating characteristic (ROC) analysis was performed and compared for elastograms and conventional ultrasound images with surgical histology as the reference standard. RESULTS: The mean age of the women was 57 years. Twenty-nine out of 50 of the nodes were histologically negative on surgical histology and 21 were positive. The sensitivity, specificity, PPV, and NPV for conventional ultrasound were 76, 78, 70, and 81%, respectively; 90, 86, 83, and 93%, respectively, for visual ultrasound elastography; and for strain scoring, 100, 48, 58 and 100%, respectively. There was no significant difference between any of the node measurements CONCLUSIONS: Initial experience with ultrasound elastography of axillary lymph nodes, showed that it is more sensitive than conventional ultrasound in detecting abnormal nodes in the axilla in cases of suspected breast cancer. The specificity remained acceptable and ultrasound elastography used as an adjunct to conventional ultrasound has the potential to improve the performance of conventional ultrasound alone.

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A recent trend in spoken dialogue research is the use of reinforcement learning to train dialogue systems in a simulated environment. Past researchers have shown that the types of errors that are simulated can have a significant effect on simulated dialogue performance. Since modern systems typically receive an N-best list of possible user utterances, it is important to be able to simulate a full N-best list of hypotheses. This paper presents a new method for simulating such errors based on logistic regression, as well as a new method for simulating the structure of N-best lists of semantics and their probabilities, based on the Dirichlet distribution. Off-line evaluations show that the new Dirichlet model results in a much closer match to the receiver operating characteristics (ROC) of the live data. Experiments also show that the logistic model gives confusions that are closer to the type of confusions observed in live situations. The hope is that these new error models will be able to improve the resulting performance of trained dialogue systems. © 2012 IEEE.

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In this letter, the uniform lying helix (ULH) liquid crystal texture, required for the flexoelectro-optic effect, is polymer stabilized by the addition of a small percentage of reactive mesogen to a high-tilt-angle (φ>60°) bimesogenic chiral nematic host. The electro-optic response is measured for a range of reactive mesogen concentration mixtures, and compared to the large-tilt-angle switch of the pure chiral nematic mixture. The optimum concentration of reactive mesogen, which is found to provide ample stabilization of the texture with minimal impact on the electro-optic response, is found to be approximately 3%. Our results indicate that polymer stabilization of the ULH texture using a very low concentration of reactive mesogen is a reliable way of ruggedizing flexoelectro-optic devices without interfering significantly with the electro-optics of the effect, negating the need for complicated surface alignment patterns or surface-only polymerization. The polymer stabilization is shown to reduce the temperature dependence of the flexoelectro-optic response due to "pinning" of the chiral nematic helical pitch. This is a restriction of the characteristic thermochromic behavior of the chiral nematic. Furthermore, selection of the temperature at which the sample is ultraviolet cured allows the tilt angle to be optimized for the entire chiral nematic temperature range. The response time, however, remains more sensitive to operating temperature than curing temperature. This allows the sample to be cured at low temperature and operated at high temperature, providing simultaneous optimization of these two previously antagonistic performance aspects. © 2006 American Institute of Physics.