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The objective of this study was to evaluate the diagnostic utility of strain and applied-pressure measurements of the median nerve in carpal tunnel syndrome (CTS). Thirty-five wrists of 23 idiopathic CTS patients and 30 wrists of 15 normal patients were examined. Median nerve strain, pressure to the skin and the pressure/strain ratio were measured at the proximal carpal tunnel level. Parameters were compared between CTS patients and controls. The areas under the receiver operating characteristic curves (AUCs) were compared for the parameters. Median nerve strain was significantly lower in the patients than in the controls (p < 0.01). Pressure and pressure/strain ratio were significantly higher in the patients than in the controls (p < 0.05: pressure, p < 0.01: ratio). The AUCs were 0.926, 0.681 and 0.937 for strain, pressure and pressure/strain ratio, respectively. Pressure/strain ratio is useful for evaluating the condition of the median nerve with respect to the hardness of the surrounding structures in CTS., (Copyright © 2017 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.)

The objective of this study was to detect differences in median nerve strain between patients with carpal tunnel syndrome and healthy controls using cyclic compression apparatus. Twenty-eight patients with idiopathic carpal tunnel syndrome and 30 normal patients were examined by ultrasound elastography. Median nerve strain, strain ratio of reference coupler and median nerve area and perimeter were measured. The areas under receiver operating characteristic curves were compared among the parameters. Median nerve strains of the patients were significantly smaller than those of the controls (p < 0.001). Strain ratios, areas and perimeters were significantly larger in the patients than in the controls (p < 0.001). The areas under curves were 0.963, 0.917, 0.759 and 0.706 for strain, strain ratio, area and perimeter, respectively. The median nerve strain had the highest area under the curve. The ultrasonic strain measurements of the median nerve provided by the cyclic compression apparatus were superior to morphologic assessment in diagnosing carpal tunnel syndrome., (Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.)

Bank failure prediction is an important issue for the regulators of the banking industries. The collapse and failure of a bank could trigger an adverse financial repercussion and generate negative impacts such as a massive bail out cost for the failing bank and loss of confidence from the investors and depositors. Very often, bank failures are due to financial distress. Hence, it is desirable to have an early warning system (EWS) that identifies potential bank failure or high-risk banks through the traits of financial distress. Various traditional statistical models have been employed to study bank failures [J Finance 1 (1975) 21; J Banking Finance 1 (1977) 249; J Banking Finance 10 (1986) 511; J Banking Finance 19 (1995) 1073]. However, these models do not have the capability to identify the characteristics of financial distress and thus function as black boxes. This paper proposes the use of a new neural fuzzy system [Foundations of neuro-fuzzy systems, 1997], namely the Generic Self-organising Fuzzy Neural Network (GenSoFNN) [IEEE Trans Neural Networks 13 (2002c) 1075] based on the compositional rule of inference (CRI) [Commun ACM 37 (1975) 77], as an alternative to predict banking failure. The CRI based GenSoFNN neural fuzzy network, henceforth denoted as GenSoFNN-CRI(S), functions as an EWS and is able to identify the inherent traits of financial distress based on financial covariates (features) derived from publicly available financial statements. The interaction between the selected features is captured in the form of highly intuitive IF-THEN fuzzy rules. Such easily comprehensible rules provide insights into the possible characteristics of financial distress and form the knowledge base for a highly desired EWS that aids bank regulation. The performance of the GenSoFNN-CRI(S) network is subsequently benchmarked against that of the Cox's proportional hazards model [J Banking Finance 10 (1986) 511; J Banking Finance 19 (1995) 1073], the multi-layered perceptron (MLP) and the modified cerebellar model articulation controller (MCMAC) [IEEE Trans Syst Man Cybern: Part B 30 (2000) 491] in predicting bank failures based on a population of 3635 US banks observed over a 21 years period. Three sets of experiments are performed-bank failure classification based on the last available financial record and prediction using financial records one and two years prior to the last available financial statements. The performance of the GenSoFNN-CRI(S) network as a bank failure classification and EWS is encouraging.