Wyniki wyszukiwania - BazTech

1

Formulation and statistical evaluation of an automated algorithm for locating small bowel tumours in wireless capsule endoscopy

Jagadeesan A., Sivaraman J.

Biocybernetics and Biomedical Engineering

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2018

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Vol. 38, no. 4

782--793

EN

Wireless capsule endoscopy (WCE) is an imaging modality which is highly reliable in the diagnosis of small bowel tumors. But locating the frames carrying tumors manually from the lengthy WCE is cumbersome and time consuming. A simple algorithm for the automated detection of tumorous frames from WCE is proposed in this work. In the proposed algorithm, local binary pattern (LBP) of the contrast enhanced green channel is used as the textural descriptor of the WCE frames. The features employed to differentiate tumorous and nontumorous frames are skewness (S) and kurtosis (K) of the LBP histogram. The threshold value of the features which offers the trade-off between sensitivity and specificity is identified through Receiver Operating Characteristic (ROC) curve analysis. At the optimum threshold, both the features exhibited a sensitivity of 100% and specificity of 90%. The skewness and kurtosis of the LBP computed from the enhanced green channel of tumorous and nontumorous frames differ significantly ( p « 0.05) with a p-value of 2.2 x 10-16. The proposed method is helpful to reduce the time spent by the doctors for reviewing WCE.

2

Using Artificial Neural Networks to Establish a Customer-cancellation Prediction Model

Huang H.-C., Chang A. Y., Ho C.-C.

Przegląd Elektrotechniczny

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2013

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R. 89, nr 1b

178--180

EN

In the past, judgments concerning customer cancellations relied primarily on managers’ experience. Prediction errors can cause surpluses or insufficient service capacity. Data mining technology can improve prediction and judgment accuracy. This study applies back propagation neural networks and general regression neural networks to establish a customer-cancellation prediction model. The empirical results showed that both prediction models possessed good predictive abilities and can aid in service capacity scheduling.

PL

W artykule opisano zastosowanie sieci neuronowych o propagacji wstecznej (ang. BPNN) oraz regresji generalnej (ang. GRNN) w budowie modelu anulowania klientów. Działanie to zwykle opiera się na doświadczeniu manager’a, co może doprowadzić do błędnych decyzji. Rezultaty badań empirycznych dowodzą dobrych własności przewidywania i możliwej użyteczności w określaniu potencjalnych działań z klientem opracowanych modeli.

3

The other thresholds in the mining association algorithm.

Kawahara M., Kawano H

Systems Science

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2000

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Vol. 26, nr 2

95-109

EN

The mining association algorithm is one of the most important data mining algorithms to derive association rules at high speed from huge databases. However, the rules derived by the algorithm contain many noises; it is then necessary for some systems to remove the noises using noise filters such as stopword lists. We improve the algorithm and develop bibliographic navigation systems using the algorithms, and we also use a dictionary to remove noises in association rules. In order to derive effective rules, it is very important to determine system parameters, such as Minsup and Minconf threshold values. We adapt the receiver operating characteristic analysis on the algorithm in our bibliographic navigation system and evaluate the performance of the derived rules. We propose extended mining association algorithms. Moreover, we evaluate the performance of our algorithms proposed using experimental database and show how our algorithms can derive effective association rules. We also show that our algorithm can remove stopwords from raw data automatically.