Neural networks : the official journal of the International Neural Network Society
May 31, 2019
This paper considers the synchronization of delayed chaotic neural networks with unknown disturbance via observer-based sliding mode control. We design a sliding surface involving integral structure and a discontinuous control law such that the traje...
Breast cancer is the most common invasive cancer in women, affecting more than 10% of women worldwide. Microscopic analysis of a biopsy remains one of the most important methods to diagnose the type of breast cancer. This requires specialized analysi...
Cell segmentation in microscopy images is a common and challenging task. In recent years, deep neural networks achieved remarkable improvements in the field of computer vision. The dominant paradigm in segmentation is using convolutional neural netwo...
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
May 31, 2019
Brain and breast tumors cause significant morbidity and mortality worldwide. Accurate and expedient histological diagnosis of patients' tumor specimens is required for subsequent treatment and prognostication. Currently, histology slides are visually...
Analytical and bioanalytical chemistry
May 31, 2019
Despite technological advances, two-dimensional electrophoresis (2DE) of biological fluids, such as vitreous, remains a major challenge. In this study, artificial neural network was applied to optimize the recovery of vitreous proteins and its detect...
The electroencephalogram (EEG) can reflect brain activity and contains abundant information of different anesthetic states of the brain. It has been widely used for monitoring depth of anesthesia (DoA). In this study, we propose a method that combine...
Lung Cancer is the leading cause of death among all the cancers' in today's world. The survival rate of the patients is 85% if the cancer can be diagnosed during Stage 1. Mining of the patient records can help in diagnosing cancer during Stage 1. Usi...
The implementation of intelligent software to identify and classify objects and individuals in visual fields is a technology of growing importance to operatives in many fields, including wildlife conservation and management. To non-experts, the metho...
Accurately predicting reference evapotranspiration (ET0) with limited climatic data is crucial for irrigation scheduling design and agricultural water management. This study evaluated eight machine learning models in four categories, i.e. neuron-base...
Allergology international : official journal of the Japanese Society of Allergology
May 30, 2019
BACKGROUND: We explored whether the use of deep learning to model combinations of symptom-physical signs and objective tests, such as lung function tests and the bronchial challenge test, would improve model performance in predicting the initial diag...
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