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Pattern Recognition, Automated

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Adaptive Learning Emotion Identification Method of Short Texts for Online Medical Knowledge Sharing Community.

Computational intelligence and neuroscience
The medical knowledge sharing community provides users with an open platform for accessing medical resources and sharing medical knowledge, treatment experience, and emotions. Compared with the recipients of general commodities, the recipients in the...

Adaptive Global Sliding-Mode Control for Dynamic Systems Using Double Hidden Layer Recurrent Neural Network Structure.

IEEE transactions on neural networks and learning systems
In this paper, a full-regulated neural network (NN) with a double hidden layer recurrent neural network (DHLRNN) structure is designed, and an adaptive global sliding-mode controller based on the DHLRNN is proposed for a class of dynamic systems. The...

A New Approach to Fall Detection Based on Improved Dual Parallel Channels Convolutional Neural Network.

Sensors (Basel, Switzerland)
Falls are the major cause of fatal and non-fatal injury among people aged more than 65 years. Due to the grave consequences of the occurrence of falls, it is necessary to conduct thorough research on falls. This paper presents a method for the study ...

Completely Automated CNN Architecture Design Based on Blocks.

IEEE transactions on neural networks and learning systems
The performance of convolutional neural networks (CNNs) highly relies on their architectures. In order to design a CNN with promising performance, extensive expertise in both CNNs and the investigated problem domain is required, which is not necessar...

Automatic identification of atherosclerosis subjects in a heterogeneous MR brain imaging data set.

Magnetic resonance imaging
Carotid-artery atherosclerosis (CA) contributes significantly to overall morbidity and mortality in ischemic stroke. We propose a machine learning technique to automatically identify subjects with CA from a heterogeneous cohort of magnetic resonance ...

Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Spectral Domain Optical Coherence Tomography (SD-OCT) is a volumetric imaging technique that allows measuring patterns between layers such as small amounts of fluid. Since 2012, automatic medical image analysis performance ...

Self-Paced Balance Learning for Clinical Skin Disease Recognition.

IEEE transactions on neural networks and learning systems
Class imbalance is a challenging problem in many classification tasks. It induces biased classification results for minority classes that contain less training samples than others. Most existing approaches aim to remedy the imbalanced number of insta...

An automatic method for lung segmentation and reconstruction in chest X-ray using deep neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Chest X-ray (CXR) is one of the most used imaging techniques for detection and diagnosis of pulmonary diseases. A critical component in any computer-aided system, for either detection or diagnosis in digital CXR, is the auto...

Margin-Based Pareto Ensemble Pruning: An Ensemble Pruning Algorithm That Learns to Search Optimized Ensembles.

Computational intelligence and neuroscience
The ensemble pruning system is an effective machine learning framework that combines several learners as experts to classify a test set. Generally, ensemble pruning systems aim to define a region of competence based on the validation set to select th...

BACH: Grand challenge on breast cancer histology images.

Medical image analysis
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...