5 resultados para positive predictive value
em Cambridge University Engineering Department Publications Database
Resumo:
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.
Resumo:
There is a widespread recognition of the need for better information sharing and provision to improve the viability of end-of-life (EOL) product recovery operations. The emergence of automated data capture and sharing technologies such as RFID, sensors and networked databases has enhanced the ability to make product information; available to recoverers, which will help them make better decisions regarding the choice of recovery option for EOL products. However, these technologies come with a cost attached to it, and hence the question 'what is its value?' is critical. This paper presents a probabilistic approach to model product recovery decisions and extends the concept of Bayes' factor for quantifying the impact of product information on the effectiveness of these decisions. Further, we provide a quantitative examination of the factors that influence the value of product information, this value depends on three factors: (i) penalties for Type I and Type II errors of judgement regarding product quality; (ii) prevalent uncertainty regarding product quality and (iii) the strength of the information to support/contradict the belief. Furthermore, we show that information is not valuable under all circumstances and derive conditions for achieving a positive value of information. © 2010 Taylor & Francis.
Resumo:
The movement of the circular piston in an oscillating piston positive displacement flowmeter is important in understanding the operation of the flowmeter, and the leakage of liquid past the piston plays a key role in the performance of the meter. The clearances between the piston and the chamber are small, typically less than 60 νm. In order to measure this film thickness a fluorescent dye was added to the water passing through the meter, which was illuminated with UV light. Visible light images were captured with a digital camera and analysed to give a measure of the film thickness with an uncertainty of less than 7%. It is known that this method lacks precision unless careful calibration is undertaken. Methods to achieve this are discussed in the paper. The grey level values for a range of film thicknesses were calibrated in situ with six dye concentrations to select the most appropriate one for the range of liquid film thickness. Data obtained for the oscillating piston flowmeter demonstrate the value of the fluorescence technique. The method is useful, inexpensive and straightforward and can be extended to other applications where measurement of liquid film thickness is required. © 2011 IOP Publishing Ltd.
Resumo:
Food preferences are acquired through experience and can exert strong influence on choice behavior. In order to choose which food to consume, it is necessary to maintain a predictive representation of the subjective value of the associated food stimulus. Here, we explore the neural mechanisms by which such predictive representations are learned through classical conditioning. Human subjects were scanned using fMRI while learning associations between arbitrary visual stimuli and subsequent delivery of one of five different food flavors. Using a temporal difference algorithm to model learning, we found predictive responses in the ventral midbrain and a part of ventral striatum (ventral putamen) that were related directly to subjects' actual behavioral preferences. These brain structures demonstrated divergent response profiles, with the ventral midbrain showing a linear response profile with preference, and the ventral striatum a bivalent response. These results provide insight into the neural mechanisms underlying human preference behavior.
Resumo:
Purpose: Although business models that deliver sustainability are increasingly popular in the literature, few tools that assist in sustainable business modelling have been identified. This paper investigates how businesses might create balanced social, environmental and economic value through integrating sustainability more fully into the core of their business. A value mapping tool is developed to help firms create value propositions better suited for sustainability. Design/methodology/approach: In addition to a literature review, six sustainable companies were interviewed to understand their approaches to business modelling, using a case study approach. Building on the literature and practice, a tool was developed which was pilot tested through use in a workshop. The resulting improved tool and process was subsequently refined through use in 13 workshops. Findings: A novel value mapping tool was developed to support sustainable business modelling, which introduces three forms of value (value captured, missed/destroyed or wasted, and opportunity) and four major stakeholder groups (environment, society, customer, and network actors). Practical implications: This tool intends to support business modelling for sustainability by assisting firms in better understanding their overall value proposition, both positive and negative, for all relevant stakeholders in the value network. Originality/value: The tool adopts a multiple stakeholder view of value, a network rather than firm centric perspective, and introduces a novel way of conceptualising value that specifically introduces value destroyed or wasted/ missed, in addition to the current value proposition and new opportunities for value creation. © Emerald Group Publishing Limited.