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  • Key words: Bile duct stones — Laparoscopic cholecystectomy — Endoscopic sphincterotomy — High-risk patient — Elderly  (1)
  • RBF neural networks  (1)
  • backpropagation  (1)
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Keywords
  • 1
    Electronic Resource
    Electronic Resource
    Prospective evaluation of a minimally invasive approach for treatment of bile-duct calculi in the high-risk patient (1997)
    Springer
    Surgical endoscopy and other interventional techniques 11 (1997), S. 632 -635 
    Details
    ISSN: 1432-2218
    Keywords: Key words: Bile duct stones — Laparoscopic cholecystectomy — Endoscopic sphincterotomy — High-risk patient — Elderly
    Source: Springer Online Journal Archives 1860-2000
    Topics: Medicine
    Notes: Abstract Background: The best approach to bile duct stones in high-risk patients is controversial. We showed in a randomized trial that open surgery had a morbi-mortality similar to that of endoscopic sphincterotomy alone (ES) and less late biliary complications. The aim of this study was to evaluate a minimally invasive approach to duct stones in high-risk patients compared with open surgery or ES alone. Methods: Sixty high-risk patients (mean age 80 years) suspected of duct stones were treated by ES + laparoscopic cholecystectomy (LC). High-risk factors were: age 〉 70 years, Goldman cardiac index 〉 13, chronic pulmonary disease, liver cirrhosis, neurologic deficit, and severe obesity. Results: ERCP success was 87%. Duct stones were found in 75%. LC succeeded in 92%. Post-LC stay was 4 days. Overall morbidity was 19% and mortality was 3%. Recurrent symptoms (mean follow-up: 9 months) was 3.6%. When compared with open surgery or ES alone, ES + LC had a similar morbi-mortality, but shorter postop stay (p 〈 0.001). Late symptoms appeared in 20% after ES alone vs 4% after open surgery or ES plus LC (p 〈 0.04). Conclusions: Combined ES + LC is an effective alternative to open surgery or ES alone for treatment of duct stones in high-risk patients.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1007/s004649900409
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    Paper (German National Licenses)
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  • 2
    Electronic Resource
    Electronic Resource
    Obtaining Fault Tolerant Multilayer Perceptrons Using an Explicit Regularization (2000)
    Springer
    Neural processing letters 12 (2000), S. 107-113 
    Details
    ISSN: 1573-773X
    Keywords: backpropagation ; regularization ; multilayer perceptron ; fault tolerance ; mean square sensitivity
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract When the learning algorithm is applied to a MLP structure, different solutions for the weight values can be obtained if the parameters of the applied rule or the initial conditions are changed. Those solutions can present similar performance with respect to learning, but they differ in other aspects, in particular, fault tolerance against weight perturbations. In this paper, a backpropagation algorithm that maximizes fault tolerance is proposed. The algorithm presented explicitly adds a new term to the backpropagation learning rule related to the mean square error degradation in the presence of weight deviations in order to minimize this degradation. The results obtained demonstrate the efficiency of the learning rule proposed here in comparison with other algorithm.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1009698206772
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    Paper (German National Licenses)
    Fulltext
  • 3
    Electronic Resource
    Electronic Resource
    Analysis of the Functional Block Involved in the Design of Radial Basis Function Networks (2000)
    Springer
    Neural processing letters 12 (2000), S. 1-17 
    Details
    ISSN: 1573-773X
    Keywords: RBF neural networks ; neural networks design ; statistical analysis of RBF ; RBF structures
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract The main architectures, learning abilities and applications of radial basis function (RBF) neural networks are well documented. However, to the best of our knowledge, no in-depth analyses have been carried out into the influence on the behaviour of the neural network arising from the use of different alternatives for the design of an RBF (different non-linear functions, distances, number of neurons, structures, etc.). Thus, as a complement to the existing intuitive knowledge, it is necessary to have a more precise understanding of the significance of the different alternatives. In the present contribution, the relevance and relative importance of the parameters involved in such a design are investigated by using a statistical tool, the ANalysis Of the VAriance (ANOVA). In order to obtain results that are widely applicable, various problems of classification, functional approximation and time series estimation are analyzed. Conclusions are drawn regarding the whole set.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1009621931185
    Library Location Call Number Volume/Issue/Year Availability
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    Paper (German National Licenses)
    Fulltext
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