AIMC Topic: Pattern Recognition, Automated
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Deep Learning Methods for Underwater Target Feature Extraction and Recognition.
Computational intelligence and neuroscience
Mar 27, 2018
The classification and recognition technology of underwater acoustic signal were always an important research content in the field of underwater acoustic signal processing. Currently, wavelet transform, Hilbert-Huang transform, and Mel frequency ceps...
Detecting oropharyngeal carcinoma using multispectral, narrow-band imaging and machine learning.
The Laryngoscope
Mar 25, 2018
OBJECTIVE: To determine if multispectral narrow-band imaging (mNBI) can be used for automated, quantitative detection of oropharyngeal carcinoma (OPC).
Deep Attention-Based Spatially Recursive Networks for Fine-Grained Visual Recognition.
IEEE transactions on cybernetics
Mar 22, 2018
Fine-grained visual recognition is an important problem in pattern recognition applications. However, it is a challenging task due to the subtle interclass difference and large intraclass variation. Recent visual attention models are able to automati...
A novel feature extraction technique for pulmonary sound analysis based on EMD.
Computer methods and programs in biomedicine
Mar 22, 2018
BACKGROUND AND OBJECTIVE: The stethoscope based auscultation technique is a primary diagnostic tool for chest sound analysis. However, the performance of this method is limited due to its dependency on physicians experience, knowledge and also clarit...
An ensemble learning system for a 4-way classification of Alzheimer's disease and mild cognitive impairment.
Journal of neuroscience methods
Mar 22, 2018
Discriminating Alzheimer's disease (AD) from its prodromal form, mild cognitive impairment (MCI), is a significant clinical problem that may facilitate early diagnosis and intervention, in which a more challenging issue is to classify MCI subtypes, i...
A pattern learning-based method for temporal expression extraction and normalization from multi-lingual heterogeneous clinical texts.
BMC medical informatics and decision making
Mar 22, 2018
BACKGROUND: Temporal expression extraction and normalization is a fundamental and essential step in clinical text processing and analyzing. Though a variety of commonly used NLP tools are available for medical temporal information extraction, few wor...
A nonnegative matrix factorization algorithm based on a discrete-time projection neural network.
Neural networks : the official journal of the International Neural Network Society
Mar 20, 2018
This paper presents an algorithm for nonnegative matrix factorization based on a biconvex optimization formulation. First, a discrete-time projection neural network is introduced. An upper bound of its step size is derived to guarantee the stability ...
Learning Temporal Information for Brain-Computer Interface Using Convolutional Neural Networks.
IEEE transactions on neural networks and learning systems
Mar 9, 2018
Deep learning (DL) methods and architectures have been the state-of-the-art classification algorithms for computer vision and natural language processing problems. However, the successful application of these methods in motor imagery (MI) brain-compu...
A Novel Neural Network Model for Blood Pressure Estimation Using Photoplethesmography without Electrocardiogram.
Journal of healthcare engineering
Mar 7, 2018
The prevention, evaluation, and treatment of hypertension have attracted increasing attention in recent years. As photoplethysmography (PPG) technology has been widely applied to wearable sensors, the noninvasive estimation of blood pressure (BP) usi...
Middle Aged
Humans
Critical Care
Hypertension
Blood Pressure Determination
Pattern Recognition, Automated
Photoplethysmography
Neural Networks, Computer
Blood Pressure
Aged
Electrocardiography
Systole
Databases, Factual
Pulse Wave Analysis
Aged, 80 and over
Diastole
Young Adult
Female
Adult
Reproducibility of Results
Male
Investigating brain structural patterns in first episode psychosis and schizophrenia using MRI and a machine learning approach.
Psychiatry research. Neuroimaging
Mar 6, 2018
In this study, we employed the Maximum Uncertainty Linear Discriminant Analysis (MLDA) to investigate whether the structural brain patterns in first episode psychosis (FEP) patients would be more similar to patients with chronic schizophrenia (SCZ) o...
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