Among various expert systems (ES), Artificial Neural Network (ANN) has shown to be suitable for the diagnosis of concurrent common bile duct stones (CBDS) in patients undergoing elective cholecystectomy. However, their application in practice remains...
We propose a novel computational method known as RVM-LPQ that combines the Relevance Vector Machine (RVM) model and Local Phase Quantization (LPQ) to predict PPIs from protein sequences. The main improvements are the results of representing protein s...
Computational intelligence and neuroscience
May 22, 2016
Quality of service, that is, the waiting time that customers must endure in order to receive a service, is a critical performance aspect in private and public service organizations. Providing good service quality is particularly important in highly c...
The research on service supply chain has attracted more and more focus from both academia and industrial community. In a service supply chain, the selection of supplier portfolio is an important and difficult problem due to the fact that a supplier p...
Computational intelligence and neuroscience
May 18, 2016
In recent years, financial market dynamics forecasting has been a focus of economic research. To predict the price indices of stock markets, we developed an architecture which combined Elman recurrent neural networks with stochastic time effective fu...
Laser speckle contrast imaging (LSCI) provides a noninvasive and cost effective solution for in vivo monitoring of blood flow. So far, most of the researches consider changes in speckle pattern (i.e. correlation time of speckle intensity fluctuation)...
Computational intelligence and neuroscience
Apr 27, 2016
In order to reduce the enlargement of coal floor deformation and the manual adjustment frequency of rocker arms, an improved approach through integration of improved genetic algorithm and fuzzy logic control (GFLC) method is proposed. The enlargement...
Medical & biological engineering & computing
Mar 25, 2016
Pulmonary tuberculosis (PTB) remains a worldwide public health problem. Diagnostic algorithms to identify the best combination of diagnostic tests for PTB in each setting are needed for resource optimization. We developed one artificial neural networ...
OBJECTIVE: Quantitative ventricular fibrillation (VF) waveform analysis is a potentially powerful tool to optimize defibrillation. However, whether combining VF features with additional attributes that related to the previous shock could enhance the ...
Predictions of patient outcomes after a given therapy are fundamental to medical practice. We employ a machine learning approach towards predicting the outcomes after stereotactic radiosurgery for cerebral arteriovenous malformations (AVMs). Using th...
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